CHARLES UNIVERSITY

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CHARLES UNIVERSITY

FACULTY OF SOCIAL SCIENCES

Institute of Political Studies Department of Security Studies

Master's Thesis

2023 Alexis Kochel

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Charles University Faculty of Social Sciences Institute of Political Studies Department of Security Studies

Master’s Thesis

Misinformation Variation? Looking Through the Gendered Lens

Name: Alexis Kochel

Academic Advisor: doc. PhDr. Vít Střítecký, M.Phil., Ph.D.

Study Programme: Master’s in International Security Studies (ISSA) Year of Submission: 2023

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Declaration:

1. I hereby declare I have compiled this thesis and only used the sources listed and, to the best of my knowledge and belief, contains no other literature that was not sourced.

2. I hereby declare the sources and literature used have been cited.

3. I hereby declare that this work has yet to be submitted previously to gain any other academic title.

In the United States, 3 January 2023 X___________________

Alexis Kochel

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Reference

KOCHEL, Alexis. Misinformation Variation? Looking Through the Gendered Lens. Praha, 2023.

_ Pages. Master’s thesis (Mgr.). Charles University, Faculty of Social Sciences, Institute of Political Science. Department of Security Studies. Supervisor doc. PhDr. Vít Střítecký, M.Phil., Ph.D.

Length of the thesis: 98,316 Characters

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Dedication:

I would love to thank many individuals that have assisted throughout this writing process. First is my family for being patient and always supportive of me throughout finishing this thesis. To all my friends who have been abroad and close, they encouraged me and were always there to lift me. In addition, the many colleagues that deserve a special thank you to Jonathon Collins, Tobias Herrmann, and Atandra Ray. Finally, I would like to thank doc. PhDr. Vít Střítecký, M.Phil., Ph.D., my advisor, for all of his assistance and diligence in the process.

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Abstract

In recent years, the growth of the far-right has been spreading across borders, becoming a major international crisis. As the far-right is growing, modern technology has become a powerful platform for recruiting members and spreading misinformation; individuals from anywhere can join, regardless of gender. As a result, women's increased number, impact, and roles within these far-right groups are expanding and becoming familiar. This thesis conducted a qualitative content analysis to depict the difference between women and men when writing messages of political misinformation online, specifically the misinformation regarding the 2020 United States presidential election. By utilizing Deborah Tannen’sThe Difference Theory, separated language-coded categories were created that depicted an established numerically and qualitatively set of differences between the discourse of the genders. The analysis described some differences between the method and meaning behind the message, but also similarities. The top used categories were the same for both genders, few were similar, and eight were different. It revealed that females expressed similarly to the males; however, males did not use the

female-oriented categories as much as the females did the males’.

Keywords

Gender, Misinformation, Far-Right, Extreme-Right, Social Media, Difference Theory, Content Analysis, Twitter, Discourse

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The 6th of January 2021 was a moment that portrayed a new state of democracy within the United States that caused an influential and significant incident revealing a rising threat to Western democracies both there and internationally. It began as a peaceful protest representing the support of Donald Trump combatting the certification of Joe Biden’s election victory, but ended in tragedy. Extremist protestors eventually besieged the Capitol building, attempting to

‘take back their country,’ which resulted in nearly 140 officers being injured and the death of five individuals (Rubin, Mallin, Steakin 2022). This event created a new image for the far-right movement and shed further light on its exponential rise in the United States.

The far-right phenomenon has been a growing research topic as the rise of activities and members have risen significantly - quadrupling in a single year between 2016 and 2017 (Jones 2018). Within this far-right phenomenon, white supremacists and anti-government extremists are classifications that have recently been on the rise (Ibid.). This terrorism has outpaced others, including those inspired by the far left, the Islamic State, and al-Quaeda (Jones, Doxsee,

Harrington 2020). In 2019, right-wing extremists were the fault of approximately two-thirds of attacks and plots within the United States and grew within the first five months of 2020 to over 90 percent (Ibid.). A few notable examples of tragedies committed by the far-right in the United States were seen in the Pittsburgh synagogue shooting in 2018, the shooting at Emanuel Africa Methodist Episcopal Church in South Carolina, and one of the most famous, Timothy McVeigh’s bomb attacks in Oklahoma City (Jones 2018). The Oklahoma City bombing was influenced by an extreme anti-governmental ideology that led to one of the deadliest attacks on American soil in modern history, killing 186 people and injuring more than 680 (Ibid.). Examples of far-right motivational attacks such as these and others that fall under the category grew significant traction

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within anti-terrorist organizations, policymakers, and researchers in the United States and other Western democracies facing similar problems.

Throughout the years previous, President Donald Trump was in office; he gained a group of highly dedicated listeners. This particular group of individuals became a heavily studied phenomenon in an attempt to understand the rhetoric and language surrounding his group's allegiance. This group gained momentum quickly and swiftly as a significant result of the internet. With the use of the internet and social media platforms, any kind of information can be disseminated globally within seconds. This speed and easy accessibility considerably changed how information is obtained and how this immediate information can affect individuals' lives.

This includes the far-right and their usage of the internet to portray their message. The internet creates a platform for extremists to utilize social media by releasing their propaganda statements, organizing possible travel for members for events and protests, recruiting and communicating with future and current members, and raising funds for support (Jones 2018).

However, this information that can be spread digitally can be factually inaccurate. This concept of incorrect information being spread brings about the subject of misinformation. The rapid spread of information that can be false and has been able to reach the minds of the general public, leads to a challenge in determining what information is presented as fact or fiction. This causes uncertainty about what is accurate [truth] and what is not, causing significant issues, such as the belief of the major conspiracy idea that the presidential election of 2020 was stolen.

Conspiracies that gain traction, such as the ‘stolen election,’ lead to the question of how misinformation within the far-right group is being spread and what is being put forth.

The political and social relevance of the far-right is an ever-growing phenomenon for many countries internationally, especially those that occur in Western democracies. It is crucial

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to understand these groups to help prevent further recruitment and possible violent attacks. This can create policies or protocols aimed toward individuals in the general public, to take away and limit rights through law, even rewarding citizens for acts against each other. These groups also range in various demographics, such as age, ethnicity, and gender. This thesis will focus on the role of gender within this demographic. The combination of the far-right, the different roles that women and men now play in modern society, and the ever-expanding reach of misinformation is a field that has limitedly been explored. With more women joining extremist groups, the social and political relevance could aim towards deradicalization protocols specific to gender to help reduce recruitment or help those already in groups. A similar bearing can also occur with

individuals on the internet, where that misinformation has a heightened pertinence on most social media platforms that should be researched. This misinformation can often influence an

individual into gaining radical ideas and becoming more radicalized by the increasing amount of misinformation to which they are exposed.

This phenomenon of gender within the far-right and the usage of misinformation then influences the aim of this thesis. Women within these groups are typically seen as background workers. However, with the use of the Internet, they too can be used as an effective tool for the far-right. Specifically, it looks into the dialogue and the content used by both women and men when spreading this far-right political misinformation and if there are any discrepancies between these dialogues.

The following research question leads this thesis in its entirety:

● What are the gender-based dialogue category differences in narrative stemming from the far-right political misinformation campaigns of the United States 2020 election?

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Due to the wide variety of misinformation campaigns, it will only examine the United States 2020 election fraud misinformation campaign and how men's and women’s discourse varied when spreading this political misinformation from 4 November 2020 to 6 January 2021.

The beginning of this thesis will provide a literature review to examine the four main aspects of this study: gender, misinformation, and the far-right, and the far-rights manifestation on the internet to describe the overall idea specifically within the United States. The literature review on gender will derive from authors from the Inter-Parlimentary Union and Susan Welch.

Misinformation review was developed by the United States Cybersecurity and Infrastructure Security Agency, Claire Wardle, Ph.D., Hossein Derakhshan, and Dean Jackson. The aspect of the far-right will be extracted from works from Dr. Benjamin Lee, Cas Mudde, and Nikki Sterkenburg. To follow, a look into the manifestation of the far right on the internet will be provided by; Manuela Caiani and Patricia Kröll for the transnationalization, Stephane J. Baele et al. showing the ecosystem, and Maura Conway, Ryan Scrivens, and Logan Macnair showing their persistent online presence. The theoretical framework will follow and will be able to provide the driving theory to explain the discourse context and create the coding categories for the methodology next set by Deborah Tannen. This methodology will provide analysis stemming from qualitative data and methods to create the body of the thesis, the analysis. The data will be sourced from fourteen randomized and unnamed Twitter accounts that have fallen under the category of believing the election was stolen and which gender category by using the profile picture, biography of the profile, or other tweets that expressed their gender. With this analysis will reveal the gender-based differential discourse patterns when spreading this information. It will show the trends and overlaps of these various discourse categorical sections between each gender. This will provide the answer to the research question of what the difference is by

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showing quantitatively displaying the statistics of tweets that fall under a category. A discussion will follow, looking into the findings and limitations of this study, and suggestions for further research, followed by the conclusion.

2. Literature Review

The literature review used to understand this thesis will be separated into gender, misinformation, and the far-right. These three topics were chosen to assist in understanding the main aim of this research. First, gender provides the basis of the thesis. Gender reveals the sociological understanding and provides the perception of the subject of the research question.

This review of gender distinguishes the two categories being studied within this research and applies it to the political field to allow an understanding of women’s participation in politics. To follow is the subject context, misinformation. The misinformation shows the methodology of disseminating the information being provided. To separate and differentiate the other types of false information is essential to reveal the subjects' motives and what is being spread by them.

For the third section, a look into the far-right will be supplied to follow the literature review. This specifies the researched realm and allows a focal area to be studied to show explicit data sets.

Fourth, a review of how the far-right has manifested online will communicate the critical historical aspect of internet usage from far-right groups, in general in the West, to display how this field of study is vital to show the relevance of this method. To conclude, a section combining gender, misinformation, and the far-right is provided to reveal the specific discipline of literature within this field that is also pivotal to continue researching as the threat of recruitment for women in extremist groups through the internet is an ever-growing operation.

a. Gender

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The concentration of gender can be seen in nearly all areas of study, ranging from science, politics, art, language, and more. Gender in politics and language will be most critical for this thesis. Women's status as political actors, participants, and activists has multiplied since the Women’s Liberation Movement (WLM) in the 1960s (Burkett 2022). The study of women in politics was not even prevalent till the 1970s as a response to the movement and pivotal events in Congress occurred for women (Burkett 2022). The outline of the framework separates into two sections: “gender” and “politics.” Gender has historically been interchanged with biological sex;

however, there are discrepancies. Although gender and sex are related, it differs from the definition of gender, which is the socially constructed characteristics that include “norms, behaviours, and roles associated with being a woman, man, girl or boy” (Kari). Sex, however, refers to the biological aspect of reproductive systems to determine whether the person is male, female, or intersex. The “politics” aspect has been defined by Oxford Learners Dictionary as the term that “the activities involved in getting and using power in public life, and being able to influence decisions that affect a country or a society,” and as a third working definition, “a person’s political views or beliefs." Gender in politics also has various realms of political focus, including their roles within governmental and political positions, voluntary participation within their political parties, policies against women, electoral manners, and many more.

Since the new movement, the study of women’s political roles has grown significantly.

According to the National Democratic Institute, the rate of global national parliaments women’s representation rate grew over the dace from 2002 to 2012 from 15 percent to 19.8 percent (Inter-Parliamentary Union: Women Map of Women in Politics 2021). However, in the

twenty-first century, the role of women within the political realm has expanded like never before (Hawkesworth 2012). The Inter-Parliamentary Union (IPU) and UN Women created a map for

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2021 to depict the role of women in politics across the globe. They represent women in

ministerial positions, portfolios held by women ministers, women in the state's highest position, women in parliament, and the world and regional averages of women in parliament

(Inter-Parliamentary Union: Women Map of Women in Politics 2021).

Susan Welch (1997) looked into the explanations for the differences between male and female political participation. She found that the idea that women are more passive politically is untrue, and they participate as much as men when there are structural and situational factors.

Married individuals and those with children have the same amount of participation between men and women; however, employment status, education, and the workforce do show a difference between men and women (Welch 1997). Unemployed and low-educated males participate more than females, but employed college-educated groups are the opposite (Ibid.). Women and men are found to be equal in voting and campaigning roles, and overall the socialization explanation does not provide any discrepancies (Ibid.). “Women may lag behind in participation because they have been discriminated against in terms of getting a good education or high paying job,” but discrimination is more direct when women run for office or are directing a campaign (Ibid.).

These discriminations could be revealed by spreading information, especially with modern technology like the internet. The internet allows anyone to speak their mind, learn anything they want, or participate in various activities.

b. Misinformation

Misleading, deceiving, or false news has been an issue for centuries globally. This type of news can range from being innocent and causing a threat of confusion, division, or undermining institutions. Through time it has been shared through newspapers, pamphlets, books, radio, and

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television which has rapidly shortened the amount of time it needs to spread and widen its audience. The invention of the internet and modern technology has excelled the dissemination of this type of information to the fastest and most widespread it has ever been, and for this thesis, it will be the focal medium.

Modern-day classification of this type of news has been separated into different

“information activities,” as listed by the Cybersecurity and Infrastructure Security Agency of the United States (2022). These activities have been split into misinformation, disinformation, malinformation, and, most recently, fake news. Exact definitions have differed through various works, but the overall meaning has remained the same. Misinformation is information activities that “[are] false, but not created or shared to cause harm” (Cybersecurity and Infrastructure Security Agency 2022). Disinformation was “deliberately created to mislead, harm, or

manipulate a person, social group, organization, or country” (Ibid.). Lastly, “malinformation is based on fact, but used out of context to mislead, harm, or manipulate” (Ibid.). The Government of Canada describes these as Mistsinformation, Disinformation, Malinformation (MDM) and describes how to identify these campaigns (Canadian Centre for Cyber Security 2022). A series of questions were created to help the public identify MDM. They can range from if it proves an emotional response, if a bold statement is being made, if it contains clickbait or if it is

exaggerated or distorted, and if it spreads virally on loosely vetted platforms (Ibid.).

Various definitions of malinformation have been created; however, it is the least studied out of the four. When researching malinformation, only a few articles are dedicated to

malinformation, and there are almost no works solely based on malinformation. Claire Wardle, Ph.D., and Hossein Derakhshan have created a report for the Council of Europe dedicated to the

“information disorder” to create a framework that will assist research and policy making. This

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work defines malinformation as “information that is based on reality, used to inflict harm on a person, organization or country” (© Council of Europe2017)¹. Examplesare moving pieces of information that could leak personal information, harassment, and involve hate speech that was supposed to stay private but made its way into the public sphere (© Councilof Europe2017).

Malinformation is not as heavily studied due to it notbeing used because of its unpopularity in use. One example used was Emmanuel Macron’semails being leaked before a run-off vote that contained accurate information to attempt to causemaximum harm to his campaign (© Council of Europe 2017). As malinformation is not as popular in its use and rare in occurrence, this will not be used for thisthesis.

Fake news is the latest terminology that has gained recent popularity from the 2016 U.S.

election, but it has yet to find a cohesive definition. First, it was used in detail on websites intentionally posting clickbait of fictional partisan content; however, the Donald Trump administration swiftly and frequently utilized the term to discredit inaccurate but unfavorable news items (Jackson 2018). Dean Jackson (2018) has generally depicted fake news as

“misleading content on the internet, especially on social media.” This content is used as a

mischievous tool in various areas, such as the economy and sometimes politics to ensure that the user is influenced to believe the information being spread is accurate with a monetary goal in mind, rather than a mentally influential one (Ibid). Tandoc Jr., Lim, and Ling (2018) categorized fake news into six typologies; news satire, news parody, news fabrication, photo manipulation, advertising and public relation, and propaganda. These categories use instances of mockery, humor, exaggeration, parody plays, fabrication, manipulation, doctored materials, and

1This intext citation was granted permission to use and had directions to include “© Council of Europe year of publication” following every statement.

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advertisement to spread fake news (Tandoc Jr., Lim, Ling 2018). However, fake news is an umbrella term that fits both mis- and disinformation, creating confusion about what fake news is (Marwick, Lewis 2017).

Disinformation is a more heavily studied phenomenon that competes with misinformation in popularity of study. There are multitudes of distinctions within the definition of

disinformation; however, the overall idea remains the same. Wardle and Derakhshan defined disinformation as “false information [that] is knowingly shared to cause harm” (© Council of Europe 2017). These could include “false context, imposter content, manipulated content, and fabricated content” (© Council of Europe 2017). Disinformation has a long history; however, modern disinformation is now the most critical. Specifically, the online realm can distort

democratic political processes by intending to deceive the general public and cause chaos (Jones 2019; Santos-D’Amorim, Miranda 2021).²A European Parliament study defined the concept as

“refer[s] to false, inaccurate, or misleading information designed, presented, and promoted intentionally to cause public harm or make a profit” (Colomina, Sánchez Margalef, Youngs 2021). The study describes that disinformation confusing and manipulating citizens creates distrust within standard institutional strategies, feeds disbelief in essential topics, and deranges elections (Ibid.). However, it is not limited to only the political realm, and it can feed into any area where vital information to the public is critical to be correct for the welfare of everyone, such as health, conspiracy theories, science, education, or history.

Misinformation overlaps disinformation in nearly every way besides the motive. Where disinformation intends to cause harm in various ways, misinformation is “when false information is shared, but no harm is meant” (© Council of Europe 2017). This type of information activity is

2Bibliographical citation is written in Portuguese, however, the content of the article is also written in English. The citation provided in the bibliography stemmed from directly the source.

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arguably the most researched and used. Various research centers, governments, and scholars have studied misinformation and provided material to the public. “Misinformation is misleading, inaccurate or completely false information communicated without the explicit intent to deceive”

(LibertiesEU 2021). Today, misinformation is easily shared and believed due to a lack of

fact-checking, education, or emotional pull (Ibid.). The spread of misinformation “has become a severe threat to public interests” due to its mass production, replication, and reach while on the internet (Muhammed, Mathew 2022). The types of misinformation overlap with disinformation:

material that misuses the context to change its meaning, fabricated content, satire that is

presented as factual, content that falsely uses different names, brands, or logos to trick people, or content that has been doctored to make it believable (News Literacy Project 2021).

Specifically, when discussing political misinformation, “prior attitudes or a political party can lead people to cling strongly to false beliefs” (Jerit, Zhao 2020). Political misinformation was first conceptualized by Kuklinski and colleagues (Kuklinski et al. 2000). In terms of welfare, they found that people have a chance of being misinformed about factual beliefs to the point that the misinformed are so confident that they are correct. One of the most critical aspects is

differentiating where the individual has “confidently held false beliefs [-] and a mere lack of information” (Ibid.). The research supported that people tend to change their political preferences in response to environmental cues, where they tend to return to their original and mistaken beliefs and preferences continually—however, this phenomenon differs from other pathologies, such as rumors and conspiracy theories (Jerit, Zhao 2020). Jennifer Jerit and Yangzi Zhao (2020) agree with Kuklinski et al. (2000) that the previous attitudes and the commitment to a political party lead to a stronger hold on false beliefs. However, they mostly dive into how

misinformation has developed unevenly over time since Kuklinski and colleagues (Jerit, Zhao

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2020). It has excelled in understanding the psychological aspects of political misinformation and where it originates from but not in how to correct the issue (Jerit, Zhao 2020). This issue of misinformation has grown exponentially due to its easy access and attainability that can be used by anyone, including members of extremist groups, such as the far-right.

c. The Far-Right

The term “Far-Right” has been consistently contested by scholars and continues to do so where “there is no consensus on terminology, and there never will be” (Mudde 2018). The term

“far-right” is usually interchangeable with “extreme right,” “right-wing,” and “radical right,”

which contains a range of ideologies and narratives that include various actors that vary in ideology or motive (Lee 2019). These interchanging of words comes from a historical context of the change in vocabulary over the decades; where it began in the 1980s with the “extreme right,”

in the 1990s, the “radical right” was more popular, and then in the early 2000s, “right-wing populism” with finally more recently the use of “the far right” (Mudde 2018). Although

examples of the far-right have been centuries before, the more modern version of this movement stemmed from the various regimes of Fascist Italy and Nazi Germany (Lee 2019). Historically and to this day, it has been drawn from conservative values and ideologies covering broad topics such as immigration, economy, politics, international orders, elites, and inequality (Halperin 2021).

Dr. Benjamin Lee overviewed the far right of an amorphous whole with various discrete groups, with ranges of ideologies and narratives over a sizable geographical context (Lee 2019).

Although he specifically studied the far right within the United Kingdom, he gives a general overview of what is qualified to fall under the far right. The various ideologies spread from fascism stemming from Fascist Italy and neo-nazism from Nazi Germany (Ibid.). In addition,

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populist and ultra-nationalist tendencies show in various groups that fall under the far-right umbrella (Lee 2019). These showed the political views as having a distinct political vision with revolutionary change to have and protect the nation from explicit corruption (Ibid.). The far-right has also noticed populism, neo-fascism, white supremacy, and authoritarian ideologies.

Specifically, he describes a key characteristic as “a narrative of racial and/or cultural threat to a

‘native’ group arising from perceived alien groups within a society” (Ibid.). The narratives he outlines are separated into six parts. The first was ananti-minority narrative, where minority groups, primarily ethnic or religious, threaten the majority of the native group (Ibid.).

Demographic threatusually falls under the immigration issue or the idea that the ‘native’

population will eventually become a minority (Ibid.). The third is thecollapse, where there is no doubt that an “ethnic or cultural strife” will occur starting from minority groups (Ibid.).

Conspiracismcategorized that there is a small working group of actors that have a malicious and vicious end (Ibid.). In their narrative's political and social aspect, the far-right hold a highly anti-elitenarrative that a small group of elites control and the far-right are being persecuted as

“victims of government oppression” (Ibid.). Lastly,historical revisionismis the idea that critical historical events were changed to suppress their ideology (Ibid.). In his comprehensive view of the ‘far-right,’ he described a “container term” for the various views, ideologies, and narratives that continue to course through the movement today (Ibid.).

Cas Mudde (2018) firsts look into the far right, understanding that “we knowwhothey are even if we don’t know exactlywhatthey are.” He specifically looks into the different types of “waves'' (third and fourth) that the far right has transformed into over the decades (Ibid.).

Specifically beginning with the third wave that was started around 1980 to 2000, where a significant rise of populist radical right parties was being voted into office (Ibid.). His

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classification of the far right covers both the radical right and the extreme right, distinct by their attitudes toward democracy (Mudde 2018). The extreme side opposes democracy in many forms, but fascism is a critical subgroup (Ibid.). The radical side accepts democracy as long as it

supports right-wing ideologies and denounces liberal democracy, i.e., pluralism and minority rights (Ibid.). The ideals of authoritarianism, populism, and nativism are mentioned as critical ideologies embedded within this sector (Ibid.). This idea is of a strictly ordered society with severe punishments, policies, and laws, demanding more police and less political involvement (Ibid.). Populism ideology, which is the focus of most of his work, is also recognized within the far right as an ideology that there should be “two homogeneous and antagonistic groups'' that would be citizens with pure intentions should be the focus of politics and a group an elite filled with corruption (Ibid.). Lastly, nativism is a merge of nationalism and xenophobia that the states should only exist exclusively for the native group and any ‘alien’ or non-native elements that threaten that state (Mudde 2017). These elements could vary from ethnicity, race, religious practice, or even defying ideas (Ibid.). Then he looks deeper into the fourth wave, which began around the twenty-first century (Mudde 2018). This was when these radical right parties were becoming accepted, established, and even regular across the globe (Ibid.). He states that overall, the fourth wave is similar to the third in most ways; however, the political context has

dramatically changed in the fourth, distinguishing the two (Ibid.). In the fourth wave, he summarizes the most critical aspects of the far right and the evolution of the movement into twelve theses (Ibid.). The first is “The Far Right Is Extremely Heterogeneous,” meaning it differs in many aspects of ideologies and activities and goes through various organizations, but still is gendered, as the eighth (Ibid.). The second, “The Populist Radical Right Is Mainstream[ed],”

meshes with the fifth that it “is increasingly normalized” (Ibid.) The third is that Populist radical

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right parties are no longer the only populist right parties that mix with the fourth; the boundaries have become blurred (Mudde 2018). The new pathological normalcy is the populist radical right and that “no country is immune to far-right politics'" standing for the sixth and ninth theses (Ibid.). For now, the populist radical right rising is leaning more toward dealignment than realignment (Ibid.). Ten through twelve all coincide with more of the current and the future, this being that the far right is here to stay where “there is no single best way to deal with the far right,” and the only way that could change is to strengthen democracy (Ibid.).

The Radicalisation Awareness Network (RAN) created a factbook to describe far-right extremism to allow the public to understand and raise awareness of the definitions of what it is, their ideologies, narratives, symbols and vocabulary, representations and manifestations, ways of recruitment through locations and motives, roles of women, and their trends and challenges (Sterkenburg 2019). They state that various definitions consist of at least five characteristics:

nationalism, racism, xenophobia, call for a strong state, and an anti-democratic attitude,” where not all are present at once but tend to encompass three ideologies that Mudde states (Ibid.). This factbook distinguishes between the radical right and extreme right; this difference is geared towards democracy. The radical right is where democracy should be maintained, and the elites must be removed, while the extreme right is that democracy needs to be replaced in a place where it is allowed to be violent against the enemies of the people (Ibid.). The factbook focuses primarily on propaganda that uses repetitive narratives to recruit people (Ibid.). Seven critical narratives were listed. These were created by Sterkenburg (2019):

1. “We are under threat.”

2. “There is a conspiracy to weaken us.”

3. “Multiculturalism will never work.”

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4. “We are not living according to our nature.”

5. “The Great Replacement.”

6. “Migrants are favored over natives.”

7. “Loss of self-government.”

These are portrayed through various symbols and messages that express these issues and have grown more online on websites, forums, social media, and message boards (Sterkenburg 2019).

RAN describes the far right as aiming to polarize society to create a gap between an “us” and

“them” mentality, separating the far right from society (Ibid.).

d. The Far Right Manifestation Online

The beginning of use of the internet by the far right started during the mid-1980s when the internet was first invented (Pauwels 2021). One of the first examples of an extremist movement utilizing the digital world was the creation of a message board namedStormfront (Baele, Brace, Coan 2020). The rapid development and the internet created various collections of online outlets, such as encrypted chat apps and message boards that are unmonitored, as well as social media sites, which has allowed for a multifaceted ability to achieve their goals (Pauwels 2021). Communications have been accelerated and hit globally due to the internet and the online social sphere, with websites such as Twitter, Facebook, YouTube, Reddit, and more. This has allowed groups, such as the far right, to have the ability to connect, communicate, and spread their ideology and subculture to others more rapidly. As “the internet does not cause

radicalization, but it helps spread extremist ideas, enables people interested in these ideas to form communities, and mainstreams conspiracy theories and distrust in institutions” (Marwick,

Clancy, Furl 2022). Where research in this field has become more prominent and prevalent in academia within the past decade, an analysis of terrorism expertise by Bart Schuurman (2019)

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revealed that overall, from 2007 to 2016, only 2% were dedicated to right-wing extremism, comparatively to jihadist concentration being one-third, but that number is now rising. This concentration of far-right extremism and its online presence has been growing, specifically within the past eight years in the United States, and is becoming a more studied topic.

Manuela Caiani and Patricia Kröll (2015) wrote an article about “the transnationalization of the extreme right and the use of the Internet.” They studied the new tactics of the extreme right “transnationalization” of “mobilization, issues, targets, action strategies, and organizational contacts” in six countries in Europe and the United States, and if the Internet plays a role in those developments (Ibid.). Within their research, they found several points. The first is that

transnational politics are being adopted by all right-wing extremist groups in their political communication or mobilization, regardless of their country of origin and nature (Ibid.). In this, they found three further points. First, “one out of three organizations mobilizes beyond the national level.” Second, the target of half of the organizations studied targeted institutions and politicians transnationally (Ibid.). Lastly, half of the groups have been shown to have contacts with similar organizations in various countries that show the cross-national threshold being crossed (Ibid.). Their second central point was that the internet is an extremely useful tool for the cross-national activation of its targets, opportunities for mobilization, and finding new far-right

“supranational organizations” (Ibid.) This proves that information and communication

technologies (ICTs) that can gather, store, transmit, retrieve, or process information digitally can reach the audience they want to target and be a multiplier to intrigue audiences outside of their norm (Computer Security Resource Center no date; Caiani, Kröll 2015). This can be explicitly seen within the United States as it was found to be the country with “the highest levels of extreme right activism on the Web” (Caiani, Kröll 2015).

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Stephane J. Baele, Lewys Brace, and Travis G. Coan research the far-right online field and see it as a multilayered, far-reaching, and heterogeneous ecosystem (Baele, Brace, Coan 2020). Filing down to four levels of analysis: entities, communities, biotopes, and whole network, they utilize it for an analytical framework to create an agenda for future research regarding the far-right and their usage of the internet (Ibid.). They found that every platform on the internet is being used to “disseminate their ideas and mobilize for action” (Ibid.). This then shows that although compared frequently to the Islamic State, as being known for having the most extensive connection to technology and internet use in their methodology, the far-right can be seen as on par in sophistication (Ibid.). However, it differs in the “quantitative production” of their content (Ibid.).

Looking at events from 2015 in the United States, such as content surrounding the election and Donald Trump, the ‘Unite the Right’ rally in Virginia, and the New Zealand mosque attack, Maura Conway, Ryan Scrivens, and Logan Macnair (2019) created a policy brief

surrounding how the Western right-wing extremists have exercised the use of the internet. This brief revealed that these extremist groups could quickly adapt when tools online were increasing and the difficulty that presented for policymakers to respond adequately to the far-right’s internet practice (Conway, Scrivens, Macnair 2019). Over 40 years, the right-wing extremists were able to establish a reliance and commitment to online forums, social media, and messaging apps that are constantly changing, and the groups are adapting to them (Ibid.). Policymakers,

nongovernmental organizations, and now government sectors are pursuing a path that will be able to combat the issue of the far-right and its spread online (Ibid.).

e. Combining The Main Three

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Gender, misinformation, and the far right are concentrations that have very little published research combining the three. Most works are based on gender and the far right or gender and misinformation, misinformation and the far right, or gender within the far right. One work that was found that combined all three was written after the January 6 attack, “The Women of January 6th: A Gendered Analysis of the 21st Century American Far-Right,” by Hilary Matfess and Devorah Margolin (2022). Within this work, a history looks into the day and event, the women that participated, and the effects (Matfess, Margolin 2022). This research took a new look into extremism for researchers, policymakers, leaders, and the general public that could provide solutions to prevent future tragedies (Ibid.). It looked deeper into women's roles within far-right extremism, specifically within the United States before and today (Ibid.). Their roles are displayed as ‘being in the background’ of extremism, where their contribution is not as forward and publicized but assistive compared to men and is more overlooked and underestimated (Ibid.).

However, within these roles, their work within these extremist groups has provided significant contributions to the group's activities, and the research displayed the example from January 6th and how gender norms affect far-right extremist events. This work then showed the modernity of these extremist groups and their movements and how they have shifted (Ibid.). Today, women are becoming more of a ‘frontline’ member, not physically but digitally (Ibid.). The use of social media has given them a new platform to reach out to anyone and everyone interested in

recruiting, and although it is not a revolutionary change to their status within far-right extremist groups, it is a change (Ibid.).

This change is critical for researchers, policymakers, and the general public to be aware of. Especially for researchers and policymakers, this new method of dissemination and tactic of spreading far-right extremism is critical to prevent further spread. In addition, the role of women

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could change more dramatically within these groups over time to become more prominent and influential in the recruitment process, especially with social media. Combining all three and studying them could reveal potential recruitment trends or techniques, possible new patterns of activity within certain far-right extremism groups, and ideological shifts that could turn global.

3. Theoretical Framework a. The Difference Theory

“Each person’s life is lived as a series of conversations” (Tannen 2007). Deborah Tannen, a University Professor and a Professor of Linguistics at Georgetown University, has written fifteen books regarding language in everyday life (Tannen no date). In her bestselling book,You Just Don’t Understand: Women and Men in Conversation, she dedicates it to the knowledge that

“therearegender differences in ways of speaking, and [we] need to identify and understand them” (Tannen 2007). The main focus is that overall, men and women have different styles of communication that can ultimately end in confusion and misunderstandings (Ibid.). This stems from the idea that boys and girls grow up differently in terms of words and talk, that by the time they grow up, it “can be like cross-cultural communication” (Ibid.). As a result, both genders speak and interpret language and messages differently. By studying honest conversations of cross-gender communications, she could outline where it went wrong and attempt to find a common language that strengthens relationships (Ibid.). This framework takes a sociolinguistic approach to see the gender differences in the patterns of these speech styles that men and women express (Ibid.).

Her other work,Gender and Discourse, published afterYou Just Don’t Understand, describes the analytical and theoretical path for how she was able to create that work. She

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utilized discourse analysis that focused on the language that connects everything within the sentence, going “beyond the sentence” (Tannen 1994). The primary notion of her work argued that “women focus on inclusion and support from others (solidarity), whereas men focus on levels of dominance and control (power) in social interaction” (Edwards, Hamilton 2004).

Within the combinations of her work, it was found that there are six major differences that women and men share when conversing that ultimately formedstatus versus support,

independence versus intimacy,advice versus understanding,information versus feelings,orders versus proposals, andconflict versus compromise(Tannen 2007).

The first isstatus versus support(Ibid.).Tannen describes first that men have grown up surrounded by conversation that is concerned with a contest where men have grown to have the urge to be first, have the upper hand, and prevent others from being able to push them around (Tannen 2016). This upbringing leads males to the conversation style that allows them to gain a certainstatusor maintain one (Tannen 2007). This differs from women, where rather than being defensive or attempting to rise above the other in conversation, women speak in a way tosupport (Ibid.). Through conversation, women use it “as a network of connections seeking support and consensus” (Tannen 2016).

Men are believed to be concerned with establishing status, which leads to a need for independence(Tannen 2007). This gives the status of “we’re separate and different” to allow the notion of status to continue (Ibid.). With independence, a feeling of resistance naturally follows (Ibid.). When an argument has arisen, independence and “freedom of action” are crucial for men (Ibid.). Women tend to counter that with what Tannen described as the vital issue for women to be interdependence, the feeling of what the other did and how it made her feel, orintimacy (Ibid.). This is the aspect of partnership, community, reaching consensus, networking, and

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connection (Tannen 2007). Individuals are no longer singular, but groups say that “we’re close and the same” (Ibid.). This would create dialogue that involves all parties to hear all sides to negotiate, connect, and support.

Adviceandunderstandingdive deep into more personal relationships (Ibid.). When listening to a problem, there follows a response under which most fall - being understanding or aiming to give advice (Ibid.). Tannen details how women want to find this connection and partnership when a personal issue has arisen, or a complaint has been made, and the partner would be understanding (Ibid.). The partner should be able to listen and give emotional support from which the woman could feel empathy and comfort (Ibid.). Within this state, it would be understood that the individuals are being reassured about their feelings with no debate. However, Tannen states that when a complaint has been made, men see it as a challenge that needs a

solution (Tannen 2016) . Finding a solution allows participation in assistance where no assistance can be given, allowing them to see what they can do to help (Ibid.).

The fourth is seen as one that is the most well-known communication confrontations (Tannen 2007). This is theinformation versus feelingscomparison (Ibid.). Growing up, when trying to find connections, women have learned to talk with more emotions, where “talk is the glue that holds relationships together” (Ibid.) Therefore, women would spend more time and commitment talking about feelings and emotions when conversing (Ibid.). This includes all types of conversation where the basis of women’s communication is led by emotion (Ibid.). When men speak, the emotional drive is not as prevalent, and they converse with facts (Ibid.). Information is used as the primary catalyst for dialogue for men, and this information mainly pertains to the world, such as politics or sports (Ibid.). Tannen articulates that women seek to build harmony amongst people, so if they are intelligent, they limit it to gain this rapport, while men want their

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status, and by portraying their knowledge of the world, being able to disseminate information can also prove a hierarchy (Tannen 2007).

The hierarchical order continues into the fifth difference,orders versus proposals(Ibid.).

As previously mentioned, this need to maintain or gain status is highly critical for men, and their course of action to do so; is to give orders (Ibid.). Giving these orders allows men to rise to be at the top and lead (Tannen 2007). “Girls don’t give orders” (Ibid.). It is claimed that women like to keep the peace and avoid confrontation, so they are more likely to give their “orders” as

suggestions, and even these “orders” are more preferences due to their lack of demand to be more likely accepted (Ibid.).

When women avoid confrontation, it leads to the final section,conflict versus compromise(Ibid.). The nature of women to be cooperative and affiliate is a common claim (Ibid.). On the other hand, when conflict arises, it threatens the connection that women are trying to build or keep, so it should be avoided (Ibid.). This is where compromises are made to resolve or prevent conflict, whereas the contrary is believed in men (Ibid.). Conflict is a way that presents negotiation of status, where it is almost nearly accepted and, if necessary, it can “even be sought, embraced, and enjoyed” (Ibid.). These differences can ultimately lead to harsh outcomes.

Tannen has presented the motives, practices, and responses and the discrepancies theorized to be perilous in how men and women speak (Ibid.). The differential upbringing of both men and women imbed a difference from youth which shows in the first,status versus support;this could be the core of what motivates men and women when conversing (Ibid.). This develops into a motivating emotional status that either rules or lacks and is presented by the will ofindependenceor the craving for connection, or how Tannen categorizes it asintimacy(Tannen

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2016). The third, fourth, and fifth categories Tannen describes under the theory are all the contrasting practices that men and women use. Men gear their conversation typology to give advice, information, or orders to feed into the status and independence for no connection (Tannen 2007). A connection drives women, so she utilizes feelings and a state of understanding with propositions to show that that leads to the responses (Ibid.). Women are more compromising in their responses, whereas men are led to conflict (Ibid.).

The chosen theory will be able to provide the framework of a gendered qualitative coded set. It will be able to reveal the ‘gender-based difference in narrative’ part of the research question by using this coded category set to categorize the tweets the men and women shared, responded to, or wrote. As the theory provides, a ‘gender-based difference in narrative’ in times of

confrontation or personal relationships could be applied in political discourse. These other meanings then will strictly relate to the political discourse of spreading misinformation regarding the 2020 presidential election as fraudulent. These create different aimed meanings for each category due to its political context, but the categories' fundamental meanings will remain the same. All twelve propositions of Tannen's theory will be utilized to create the qualitative code.

This background creates the knowledge needed to analyze the tweets to determine further meaning than solely the text alone and will show the aims of these messages being sent to see what intent should be felt by the reader.

4. Methodology

a. Conceptual Content Analysis

Content analysis is a methodology developed and mainly used in various concentrations ranging from sociology to communication that allows interpreting and analyzing texts, symbols,

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images, and other open-source data to determine multiple meanings. However, the media's

creations have changed the content analysis look. The first example of content analysis stemming from the media appeared in 1787; a political commentary critiqued an anti-Federalist essay in The New Hampshire Spythat listed words and counted how many times they appeared in the article (Macnamara 2018). However, the work of Harold Lasswell, one of the most influential contributors to content analysis, skyrocketed the use of content analysis in history (Neuendorf 2002). Although his first work analyzing World War I propaganda was retracted as a content analysis by himself, he continued to develop content analysis with a group of others who assisted in World War II to estimate where German troops were in Europe (Ibid.). By the 1950s, the realm began to skew and enter the world of psychology, and then it became critical to understand individual texts for psychotherapeutic purposes (Ibid.). This coincided with the work of Bernard Berelson, who publishedContent Analysis in Communication Research, which specifically gained traction for using this tool in social sciences and media in 1952 (Prasad 2008). He defines content analysis as “a research technique for the objective, systematic, and quantitative

description of the manifest content of communication” (Muhammed, Mathew 2022). Another primary developer of content analysis is Klaus Krippendorff, who has dedicated decades to this research. He encompassed Berelson’s definition and defined content analysis as “a research technique for making replicable and valid inferences from data to their context” (Krippendorff 1989). His most recent work was published in 2018 and is used as the framework for various researchers in multiple fields. Robert Weber (1976) also developed a version stating that “content analysis is a research method that uses a set of procedures to make valid inferences from text.”

These researchers developed a methodology that has increased exponentially over the decades and is used by researchers in many concentrations.

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Content analysis can either be qualitative or quantitative. These methods share many aspects of the methodological process but do have differences. According to Bertram Scheufele (2008), there are two main differences. The first is how they are measured (Scheufele 2008).

While using textual material as data, quantitative analysis breaks it down into different elements but utilizes numeric coding to categorize it (Ibid.). This differs from qualitative by putting the text materials into organizing units and labeling them (Ibid.). The second Scheufele (2008) mentions is the amount of data that is being utilized. Quantitative tends to deal with larger quantities of data and material where numbers can describe the categories and the analysis frequency in more detail (Scheufele 2008). On the other hand, qualitative content analysis tends to be limited in the amount of text material and uses them hermeneutically (Ibid.). Qualitative research is used to understand the text's other meanings and concepts.

Marilyn Domas White and Emily Marsh have created a summary of both quantitative and qualitative content analysis; however, for this thesis, only qualitative content analysis will be used. White and Marsh use Krippendorff’s work as their basis for the definition from 2004, “a research technique for making replicable and valid inferences from texts (or other meaningful - matter) to the contexts of their use” (White, Marsh 2006). To get into the actual methodology, they separate the text and the context as independent sections, and one concludes one to the other (text to context) (Ibid.). Texts allowed in content analysis use linguistic elements in a linear fashion that follows the rules of grammar and various devices to create a cohesive,

understandable message (White, Marsh 2006). Within these texts lies meaning that may depend on the recipient's understanding because it is not evident linguistically (Ibid.). There needs to be coherence and intention within the text to be accepted and to give “new or expected

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information,” and when written must be written with an understanding of its surrounding text to produce an accurate message of display of meaning (White, Marsh 2006).

Nine aspects are considered when outlining the methodology. The first two are to create the research question, which will guide all of the data gathering and the analysis itself in a naturalist or humanist interpretive manner (Ibid.). Then, when selecting the data for the sample, it must have “syntactic, semantic, or pragmatic categories” and give answers to the research questions that can continue throughout the research and reveal “the big picture,” and show the objective as the third, fourth, and fifth (Ibid.). Categorizing the data is the sixth step to

exemplifying the critical concepts or patterns that reveal the research question's answer.

Categorizing and collecting the data will need the coding of the data, which is subjective, and will need to demonstrate the outcome for the “argument basis of proof” for the seventh and eighth (Ibid.). The last is whether computers will be used or not to assist in the search or count the data (Ibid.).

These aspects of consideration are critical when following this methodology. An essential point of qualitative analysis is that it cannot be generalized (Ibid.). Still, how it transfers, not all data must “have an equal or predictable probability of being included in the sample” (Ibid.). The internal validity of the data should represent all the critical factors of the research question, and the data analyzed from various data sources and perspectives should reflect that and where the results are dependable, replicable, and transferable from one context to another (Ibid.).

b. Data Collection and Analysis

This thesis utilized and followed all of the steps in the methodological process as

described above. First, the text medium chosen for the data selection was Twitter; this was due to the previous President Trump’s usage of the networking platform and its widespread modern-day

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usage. Twitter allows individuals to post various messages on the public forum that anyone can read unless it has been censored, the tweets are protective, the profile is private or was deleted, or the author limited its viewers. Since 2017, these messages have grown from allowing 140

characters to 280 characters within a single tweet (Boot, Tjong Kim Sang, Dijkstra, Zwaan 2019). Within these tweets, you can create your messages or respond to responses written by others to send out whatever information you want to provide.

The selection of profiles was based on the theme of election fraud. Specifically, these profiles showed support or shared messages positively relating to election fraud. In this instance, positively means that their messages interpreted belief in the election fraud. Therefore, the objective was to find profiles that shared or produced tweets supporting election fraud misinformation. From there, the gendered lens needed to be provided. Within Twitter, each profile can upload a picture to show who the individual is; this is their ‘profile picture.’

Therefore, looking at the ‘profile picture’ and using their names and written biographies could determine if they were a woman or a man. This determination is an assumption from these to then categorize. An additional search of how many followers each profile had was considered.

The more followers the author of the tweet has, the higher likelihood of it reaching a different audience on the platform. The profiles had a minimum of 100,000 followers to up to 7 million.

This helped in assisting which profiles would have more traction. The profiles did not have to be

‘verified,’ meaning that the individual took steps to verify that they were the rightful owner of the account; however, it had gained traction over the years as a label of social status. Once the profiles were selected, a manual look through the tweets was initiated.

The manual search looked for tweets representing the objective of tweets fitting into the categories set. The tweets compiled for the data were placed in a time frame from 4 November

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2020 to 6 January 2021. This time was the prime for spreading misinformation regarding the election and the gradual build-up to the Capitol Riot. Then to reveal the aim of the study, Tannen’s theory provided the coding categories to see if the patterns found in her research also replicated in individuals' dialogues in far-right politics. These then looked into the semantics of the tweets being produced or reproduced to see if they followed the patterns that Tannen

provided;Status,Independence,Advice,Information,Orders, andConflict. The same was done for the female profiles, with their categories listed as;Support,Intimacy,Understanding, Feelings,Proposals, andCompromise. Both classes are listed below to describe what meanings were searched for within the tweets to provide proof of analysis for the research question about the misinformation on election fraud.

For males as created by Tannen (2007):

1. Status- These tweets gave a message that asserted an individual's social rank or status or created a higher one for them when produced or in response to a tweet. In addition, it could attack another one’s status.

2. Independence- They portrayed a sense of will for autonomy from the event and others.

3. Advice- A recommendation was made from a personal opinion or standpoint.

4. Information- Factual information was at the forefront of the message.

5. Orders- Demands were asserted to others.

6. Conflict- They introduced an understanding of a struggle, clash, or serious disagreement that could be subtle or forward. It also included creating a conflict with one another.

While to counter this, the female categories, also inspired by Tannen (2007):

1. Support- Provided a feeling of reinforcement to the ideas of election fraud or to individuals promoting election fraud (Ibid.).

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2. Intimacy- These sent messages relating to others sharing the news (Ibid.).

3. Understanding- Sympathetic feelings were portrayed throughout the messages to others (Ibid.).

4. Feelings- Feelings and emotions led the message or wanted the reader to create a feeling (Ibid.).

5. Proposals- A recommended suggestion that does not stem from an opinion (Ibid.).

6. Compromise- Rather than fighting disagreements, alternative responses were given (Ibid.).

Over 70 profiles were researched, and tens of thousands of tweets were compiled.

However, to look deep behind the meaning of the tweets, only fourteen profiles were utilized, and 1,065 tweets were manually analyzed. These tweets either mentioned the election fraud or responded to other tweets concerning it. Once all the tweets were collected, they were singly put into these twelve categories to portray whether the tweets supported the theory or not

numerically. These tweets overlapped in categories, having a single tweet fit into multiple categories and cross the gender boundary. This means numerous tweets written by men also fit into the female-coded category and vice versa. To begin the categorized data, each tweet was interpreted and accounted for in every section that it fit. Once each was categorized, it revealed how many tweets out of how many tweets total written by each profile provided the qualitative data in that category. Then, each profile's percentage of the coded type was created to reveal how many tweets of the profile fit into any of the twelve—using the formula: X/Y = Px100. X represents the number of tweets that fit into the particular category being calculated, while Y represents the total tweets that that profile wrote within the timeframe. The percentage given can

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give a numerical answer to the qualitative data of categories to determine if there is a pattern of men and women utilizing language differently when spreading misinformation, as shown below.

5. Analysis

The analysis can be provided by collecting background information from the literature review and understanding the methodology presented. The examination will be put into sections to see the differences and similarities between language use and its gendered difference. It will also reveal some non-specific examples that demonstrate the overall idea. The usage of

non-specific models keeps the profiles anonymous but still exemplifies the meanings behind the messages. The first two will be of different genders: women and then men. This is strictly to go deeper into the data of each gender and look into the most influential categories. This thesis will mention no names, regardless of the knowledge that Twitter is a public platform available to anyone. Instead, examples will be given, and profiles will be listed as a number set, i.e., Profile 1, Profile 2, and so on. Then to finalize the data set, there will be an analysis comparing the categories of the two to show if there is a gender-based difference in the political narrative.

a. Profiles of Men

Eight profiles were selected for the men, and a total of 534 tweets were examined and analyzed. Of these 534 tweets, nearly every tweet overlapped the categorical codes. Therefore, table 2 gives the percentage of the male profiles.

Table 1

Percentage of the Men’s Profile’s Codes

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As can be seen, the first six categories are those that Tannen (2007) described as dominated by men and the last six by women. The top three highest categories overall were Conflict,Information, andStatus,with the lowest beingProposals,Compromise, andFeelings.

Nearly every profile had over fifty percent of their tweets presenting a conflict towards another, or they recognized a conflict that was either subtle or forward. These could have been towards an individual or a group, creating a conflict by using historical examples to compare to today or questioning what is happening. An example of different events in comparison is that there are many more of ‘China influencing the election’ towards Democrats than ‘Russia influencing the election,’ linking the historical example of the investigation into Russia and the impact on the 2016 election (Profile 1), Thus, comparing the same believed event of voter fraud but against the Democratic party; even stating about Republicans and their refusal to fight will threaten if there will ever be a Republican president again (Profile 1 and Profile 4). The meaning of fighting or presenting conflict was repeated excessively throughout the data and the profiles. When the conflict was set directly against one another, it was mainly against the media, spokespeople against the idea of fraud occurring, Democrats, Joe Biden and his team, or even the general

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public. Many tweets were centered around the ‘us versus them’ mentality, in which the natural defensiveness created a sense of conflict. A common theme was that there was little belief that Joe Biden outnumbered Donald Trump in the votes due to his little campaigning. They compared these examples mostly syntactically in the form of complicated questions but semantically creating a conflict. For example, ‘going to total war for the integrity of the election’ but how it was possible to be in that position in the first place and attack ‘them’ (Profile 5).

This disbelief that Biden could outnumber Trump was heavily reinforced using statistics, categorized underInformation.Informationused historical facts, statistics, or even individual quotes to support their messages. Although these types of information are used to be factual, this study is researching misinformation, which is false information. Due to that, it does not matter if it is accurate or inaccurate; it is the “facts” application that matters to infer that the information is being used correctly and that the authors of the messages genuinely believe that these are facts.

An irrefutable fact was the articles used by the Constitution as an authentic document and foundation for the United States. This document frequently referred back to show the errors of the process, such as deadlines, and how the legislatures have a constitutional duty to follow it and go through with the investigation. Another heavily used example was comparing the

statistics of Barack Obama's votes against Donald Trump and Joe Bidens throughout the election process in different areas. This revealed statistics that the profile questioned as to how the

numbers were possible. Statistics do not compare the candidates, just using the statistics and stating that they are impossibilities. Using the updates occurring as recounts ensued was highly popular as examples to update everyone on the current status and show the occurring

discrepancies. Various news sources, such as Newsmax, were highly used to report these changes and voter fraud and irregularities. Where lost and found ballots were, they wereonlyfor Biden,

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broadcasting a statisticalimpossibility.This information is a catalyst for showing mistakes that benefit the ‘them.’ When individuals shared other facts that argued with the ones the profile utilized, their intelligence came into question.

People’s intelligence within debate fell underneath theStatuscategory.Statusinferred to someone’s intelligence or position that was either attacked came into question or used as a way to represent further corruption. This is where people with political power, such as state

legislatures, senators, presidential candidates, or lawyers, and their status were used as a negative or a positive. It would question why people in these positions of power were not doing anything to fight the fraud or show how they are using their work to assist in the fraud. Individuals that were also in the media were seen as actors of high status. This is because that is how the general public receives their information and is seen as an outlet for trustworthy information. Many tweets were dedicated to either informing about the role that the media is holding in

‘brainwashing’ the public, the information they are giving out is false, or other media outlets are the only source of true knowledge. For example, Fox News was under scrutiny for not boosting the information regarding the occurring fraud. Many were told to stop watching Fox and move to other sources promoting it. Journalists then were ridiculed for their intelligence for not

supporting or being seen as genius for reporting the facts. This also pertains to anyone within the general public that responds to profiles, especially in a negative light, calling anyone ‘stupid,’ an

‘idiot,’ or ‘insane,’ influencing a sense of feeling.

b. Profiles of Women

Feelingswere one of the most used categories in the women’s data. The data set analyzed six profiles and 531 tweets. In Table 2, the data is given from the percentage of each code per profile.

CHARLES UNIVERSITY