Doctor of Philosophy (Ph.D.), Bowling Green State University, 2023, Media and Communication

This dissertation investigates the effectiveness of counterspeech strategies employed on Twitter in response to anti-Asian hate during the COVID-19 pandemic. This research delves into the communicative strategies, emotional tones, and geospatial distribution of counterspeech, specifically focusing on its effectiveness in the United States. A supervised machine learning was employed to classify counterspeech tweets and counterspeech strategies based on empirical typology. By analyzing 106,388 tweets associated with the hashtag #StopAsianHate collected from November 2021 to May 2022, this research provides insights into the varied effectiveness of counterspeech strategies. The analysis revealed that though counterspeakers were using more negative tones in counterspeech tweets, the tweets with visual media and positive emotional tone received more engagement on Twitter through retweets and favorites compared to those with a negative or neutral tone. This study also breaks new ground by recognizing that higher level of racial diversity does not facilitate higher level of counterspeech against hate speech and hate crime. Additionally, this study highlights the varying degrees of participation in counterspeech across different ethnic groups within Asian American community and underscores the importance of tailored strategies in addressing hate speech. Recognizing this distinction proved essential in crafting evidence-based guidance for community and individual interventions while fostering support from allies of diverse racial backgrounds.

Committee: Louisa Ha Ph.D. (Committee Chair); Lisa Hanasono Ph.D. (Committee Member); Yanqin Lu Ph.D. (Committee Member); William Sawaya Ph.D. (Other) Subjects: Artificial Intelligence; Asian American Studies; Communication; Mass Media; South Asian Studies

Master of Science (MS), Wright State University, 2017, Computer Science

The crime and violence street gangs introduce into neighborhoods is a growing epidemic in cities around the world. Today, over 1.4 million people, belonging to more than 33,000 gangs, are active in the United States, of which 88% identify themselves as being members of a street gang. With the recent popularity of social media, street gang members have established online presences coinciding with their physical occupation of neighborhoods. Recent studies report that approximately 45% of gang members participate in online offending activities such as threatening, harassing individuals, posting violent videos or attacking someone on the street for something they said online in social media platforms. Thus, their social media posts may be useful to social workers and law enforcement agencies to discover clues about recent crimes or to anticipate ones that may occur in a community. Finding these posts, however, requires a method to discover gang member social media profiles. This is a challenging task since gang members represent a very small population compared to the active social media user base. This thesis studies the problem of automatically identifying street gang member profiles on Twitter, which is a popular social media platform that is commonly used by street gang members to promote their online gang-related activities. It outlines a process to curate one of the largest sets of verifiable gang member Twitter profiles that have ever been studied. A review of these profiles establishes differences in the language, profile and cover images, YouTube links, and emoji shared on Twitter by gang members compared to the rest of the Twitter population. Beyond the earlier efforts in Twitter profile identification that utilize features derived from the profile and tweet text, this thesis uses additional heterogeneous sets of features from the emoji usage, profile images, and links to YouTube videos reflecting gang-related music culture towards solving the gang member p (open full item for complete abstract)

Committee: Amit Sheth Ph.D. (Committee Co-Chair); Derek Doran Ph.D. (Committee Co-Chair); Krishnaprasad Thirunarayan Ph.D. (Committee Member) Subjects: Computer Science

Master of Arts (M.A.), University of Dayton, 2024, Theological Studies

This thesis examines the influence of conspiratorial content present throughout American Catholic digital spaces. Drawing on several contemporary definitions of contemporary conspiracism, the thesis first identifies rhetorical hallmarks of digital conspiracism in places like social media feeds and blogs, including accusatory claims about power; binary framings; and aesthetic invocations of violence and eschatological judgment. Based on these definitional grounds, the thesis conjectures a disproportionate amount of existent conspiratorial rhetoric in primarily English-speaking Catholic digital spaces compared to estimates of total participants within #CatholicTwitter and adjacent digital spaces. The first chapter affirms the many benefits media and connective technologies bestow on contemporary societies. It largely agrees with works like Katherine G. Schmidt's Virtual Communion which highlight how concepts like mediation and virtuality—both key to internet functionality—lie at the heart of Catholic theological understandings of reality. Given those two points and the initial conjecture, the thesis asks the following question: if digital interactions are real (albeit nuanced) parts of human life, what should scholarly observers and institutional leaders alike make of the conspiratorial fragments floating between cyber and "real-life" conversations? Utilizing an interdisciplinary methodological approach drawing on Catholic intellectual history, recent social science research, and theological reflection, the rest of the project tries to answer that question. In answering it, the project warns institutional American Catholicism might yet fail a twenty-first century "stress test" alongside other contemporary institutions. The second chapter examines historical conditions in the twentieth and twenty-first centuries during which emergent media technologies helped polarize ideas and detach individuals from their immediate communities. It also contrasts institutional C (open full item for complete abstract)

Committee: William V. Trollinger (Advisor); Nicholas Rademacher (Committee Member); Vincent J. Miller (Committee Member) Subjects: Religion; Theology

Doctor of Philosophy (PhD), Ohio University, 2024, Mass Communication (Communication)

This study addresses a notable gap in the existing literature by investigating the securitization processes employed by populist politicians through social media channels. Focusing on the social media accounts of two prominent NATO member country leaders, Recep Tayyip Erdogan of Turkey and Donald Trump of the United States, the research analyzes posts that incorporate both populist and security-related themes on Twitter. The central objectives are to ascertain the frequency of such posts, identify the prevalent themes, and explore the similarities and differences in the detected themes across the twelve months of the last two election periods. The collected data underwent chronological organization to discern patterns in the frequency of these posts. For each sub-theme, the researcher selected tweets that most strongly represented the theme, subjecting them to thematic analysis. The findings indicate a heightened frequency of securitizing tweets by populist politicians as the elections get closer. Both leaders demonstrated engagement with the identified themes, revealing a nuanced approach that is influenced by their distinct linguistic and political-cultural backgrounds. Notably, the study unveils instances where these politicians, despite differing languages and political cultures, framed certain issues similarly while adopting communication methods incongruent with each other's framing styles. This research contributes valuable insights into the intersection of populism, securitization, and political communications, shedding light on the nuanced dynamics observed in the online discourse of populist leaders from diverse geopolitical contexts.

Committee: Jatin Srivastava (Advisor); Benjamin LaPoe (Committee Member); Amy Chadwick (Committee Member); Nukhet Sandal (Committee Member) Subjects: Communication; Journalism; Mass Communications; Mass Media

Master of Computing and Information Systems, Youngstown State University, 2023, Department of Computer Science and Information Systems

Investors are always looking for ways to make profit in the stock market. Predicting this highly volatile market has been historically challenging. This study explores the use of the social media platform, Twitter, and Machine Learning Algorithm for Time Series Analysis. Our findings suggested that Twitter's data may not be the best for Sentiment Analysis, while other machine learning techniques for Time Series Analysis such as LSTM would be effective. This could potentially help an investor with higher returns.

Committee: John R. Sullins PhD (Advisor); Feng George Yu PhD (Committee Member); Alina Lazar PhD (Committee Member) Subjects: Artificial Intelligence; Computer Science

MS, Kent State University, 2022, College of Arts and Sciences / Department of Computer Science

Drug epidemics have been a major problem in the United States for decades. As of August 2022, recreational marijuana can be legally purchased in 19 states in the U.S and medical marijuana is legal in 37 states. The forward legalization of marijuana in states is a factor of increasing social media content about marijuana use among young adults. Widespread promotion of alcohol, tobacco and substances in social media and other forms of entertainment change social norms. A number of research groups study drug abuse contents on social media such as Instagram, Reddit, YouTube, Facebook and Twitter. Some researchers study drug abuse in popular songs and popular music videos. Yet none have discussed drug abuse lyrics on social media. In this study, we carry out our novel detection of drug-related lyrics on Twitter through two different approaches, the Smith-Waterman algorithm and natural language processing algorithm. We analyzed over 1.3 billion publicly available tweets from 2016 and 2017 to identify substance use lyrics. We collected 101,117 tweets that are references to substance use lyrics. The local sequence alignment algorithm or the Smith-Waterman algorithm can identify drug abuse lyrics with accuracy up to 81% where a machine learning algorithm, Long Short Term Memory (LSTM), can identify with accuracy up to 48.9%.

Committee: Ruoming Jin (Advisor); Jong-Hoon Kim (Committee Member); Michael Carl (Committee Member) Subjects: Computer Science

Doctor of Philosophy (Ph.D.), Bowling Green State University, 2022, Media and Communication

This dissertation seeks to understand how sports fans organize, mobilize, and interact through social media to discuss protests against sports league policies that fans believe to be unjust. In our case, Major League Soccer (MLS) instituted a new league policy in 2019 that in general, banned political speech within MLS stadiums. After reports of hateful chants and instigations of violence in MLS stadiums from far-right hate groups, MLS fans began rallying around the anti- fascist symbol of the Iron Front in hopes to deter the hate groups from entering the stadiums. Major League Soccer perceived the Iron Front imagery to fall under their prohibition of political speech and began to ban fans that displayed the symbol of the Iron Front at MLS matches. Utilizing the theoretical lenses of Critical Race Theory (CRT), Political Process Theory (PPT), Image Restoration, and Dialogic Communication, this study examines how fan-driven social movement form, how they achieve their goals, and how sports leagues respond with particular reference to MLS. Through the implementation of Critical Discourse Analysis, posts and comments relating to the Iron Front protests from MLS subreddit, r/MLS, as well as related Twitter posts were examined to monitor fan reactions. Additionally, Tweets from multiple official MLS accounts were investigated to gauge any public acknowledgement of the protests. Overall, the Iron Front protests, which I have called the New Iron Front due to their co-opting of the anti-fascist symbol, formed an anti- racist and anti-fascist social movement which incorporated several key aspects of CRT. Other findings indicated that the New Iron Front both created and took advantage of political opportunities that became available as they engaged in protests against league policy. From a public relations perspective, Major League Soccer severely underestimated the strength and longevity of the New Iron Front movement. As a result, MLS was forced into multiple strategi (open full item for complete abstract)

Committee: Ellen Gorsevski Ph.D. (Committee Chair); Kefa Otiso Ph.D. (Other); Lara Lengel Ph.D. (Committee Member); Terry Rentner Ph.D. (Committee Member) Subjects: Communication; Multimedia Communications; Sports Management

MS, University of Cincinnati, 2022, Education, Criminal Justice, and Human Services: Information Technology-Distance Learning

As technology permeates day-to-day life, people have more and more ways to communicate. These forms of communication create a challenge for Public Safety Answering Points (PSAP). Research has shown people are posting on social media for medical help, but PSAPs do not have a way to receive these messages. This research aims to determine if using keywords and filter words can be used to find the actionable calls for help in the midst of the millions of posts made. Actionable is defined as containing enough information to determine the nature of a medical emergency and if is currently occurring or is recent enough that the poster needs help. To determine if this was true, the most prevalent types of voice medical calls to the Cincinnati Fire Department were determined for 2021. A set of keywords and filter words was created for each call type. Then tweets were captured over a period of seventeen hours and filtered using the word lists. The filtering showed there was a valid way to find actionable tweets, and that people were posting such things. By varying the word lists, the signal-to-noise ratio can be adjusted depending on the desires of the agency. as filtering became more strict, the number of missed actionable tweets increased, while the number of incorrectly labeled as actionable decreased.

Committee: Jess Kropczynski Ph.D. (Committee Member); Shane Halse Ph.D. (Committee Member) Subjects: Information Technology

Master of Science, The Ohio State University, 2022, Psychology

Many people with mental illness do not receive treatment (Reinert et al., 2021). Even when they do, 30-50% dropout prematurely (Roos & Werbart, 2013). One barrier to treatment seeking and uptake is the belief that nothing can be done about the symptoms. Not only is such a belief likely to deter treatment seeking, but it may also serve to undermine the treatment options available. Those who see depression or anxiety symptoms as stable or even innate are presumably less likely to actively engage in, and therefore benefit from, treatments that rely on patient-initiated behavior (e.g., modifying cognitions and behaviors). Carol Dweck (2006) highlighted the role of fixed and malleable mindsets in the context of studying children's beliefs regarding intelligence (Hong et al., 1999). Specifically, her research team found that children who viewed intelligence as a malleable feature that can be improved upon with effort performed better academically than those who believed intelligence is fixed and not amenable to change. Subsequent studies have shown that malleable mindsets are associated with fewer symptoms of depression and anxiety, lower negative emotionality, and less psychopathology in general (De Castella et al., 2013; Tamir et al., 2007; Schroder et al., 2019). Additionally, given the widespread use of social media to disseminate information about important issues, including psychological health, we sought to understand how the influence of social media communication regarding mental health impacts viewers' own beliefs about mental illness recovery. To do this, we conducted an experimental study with 321 student participants from a large Midwestern university. Participants were randomized into one of three conditions – fixed, malleable, or positive affect – and viewed a series of fictitious tweets. In the fixed condition, participants viewed tweet content presenting mental illness from a fixed mindset perspective. The malleable condition included tweet content presen (open full item for complete abstract)

Committee: Jennifer Cheavens (Advisor); Kentaro Fujita (Committee Member); Daniel Strunk (Committee Member) Subjects: Clinical Psychology; Psychobiology; Social Psychology

Master of Arts, Case Western Reserve University, 2022, Cognitive Linguistics

Given the role of distributional semantics in child language acquisition, adult linguistic development, and the conceptualization of abstract entities, the present investigation seeks to explore if the variable frequency of linguistic utterances across clusters of users in a social network can be correlated with divergent interpretations of an ostensibly shared concept within a discursive community. Are differing rates of linguistic entrenchment within a community a marker of divergent conceptualization? To begin to address this question, this present pilot study details the socio-cognitive processes underlying entrenchment of language and concepts, and develops a method for studying divergent conceptualization in the online social media network Twitter.

Committee: Vera Tobin (Committee Chair); Todd Oakley (Committee Member); Mark Turner (Committee Member) Subjects: Linguistics; Multimedia Communications; Social Psychology

Master of Science (MS), Wright State University, 2022, Biological Sciences

This study assesses the underlying topics, sentiment, and types of information regarding COVID-19 vaccines on Twitter during the initiation of the vaccine rollout. Tweets about the COVID-19 vaccine were collected and the relevant tweets were then filtered out using a relevancy classifier. Latent Dirichlet Allocation (LDA) was used to uncover topics of discussion within the relevant tweets. The NRC lexicon was used to assess positive and negative sentiment within tweets. The type of information (information, misinformation, opinion, or question) in tweets was evaluated. The relevancy classifier resulted in a dataset of 210,657 relevant tweets. Eight topics provided the best representation of the relevant tweets. Tweets with negative sentiment were associated with a higher percentage of misinformation. Tweets with positive sentiment showed a higher percentage of information. The proliferation of information and misinformation on social media platforms are associated with building trust and mitigating negative sentiment associated with COVID-19 vaccines.

Committee: William Romine Ph.D. (Advisor); Jeffrey Peters Ph.D. (Committee Member); Paula Bubulya Ph.D. (Committee Member) Subjects: Biology; Epidemiology; Health Education; Health Sciences; Public Health; Public Health Education

Bachelor of Science of Journalism (BSJ), Ohio University, 2022, Journalism

On January 6, 2021, while Congress was certifying the electoral college votes that would certify Joe Biden as the next president of the United States, sitting president, Donald Trump, held a rally. The presidential election, held during the height of the pandemic, was the topic of controversy as President Trump spread lies about voter fraud from mail-in ballots. Twitter was used throughout the election season as a way for President Trump and his supporters to spread misinformation regarding the legitimacy of the election, and later, Joe Biden's win. All of the rumors and lies culminated on the day of the certification, as angry Trump supporters stormed the Capitol, breaching the building and causing an evacuation of staff. Many people were injured, some died, and around 800 people were charged in connection with the riot. Additionally, President Trump and 70,000 other users were banned from Twitter for spreading misinformation. This thesis focuses on the aftermath of the event and the subsequent rally held on September 18, 2021 in support of the people who were criminally charged. Using a social media analysis of Twitter from 11 a.m. to 3 p.m. that day, the aim was to analyze Twitter discourse around controversial events and compare First Amendment rights to escalation of events on social media. The findings suggest that Twitter is not a tool for escalation, rather people find like-minded groups on Twitter and tailor their content towards them, with no intention of interacting with opposing viewpoints. This creates an environment where users feel like they have the freedom to say whatever they want, no matter how aggressive or damaging, without consequence.

Committee: Aimee Edmondson (Advisor) Subjects: Journalism; Law; Mass Media; Multimedia Communications

Bachelor of Arts, Walsh University, 2022, Honors

Each year social media usage increases which creates new opportunities for marketers to promote their products and brands. Sports teams and athletes are joining social media platforms and creating their own unique accounts (Cooper, 2015). Fans and followers, new and old, are discovering these teams and athletes while building relationships (Kentrin, 2020). Social media has also proven to be a useful tool in building two-way relationships between teams and spectators (Joanna & Zuzanna, 2020). This has also reigned true in building a team or personal athlete brand (Witz, 2020). Through different sports marketing social media strategies, marketers are learning how to engage fans, increase attendance, and stand apart from other teams (O'Hallarn et al., 2016). The manner in which a fan behaves and engages with different teams and athletes is influenced by social interactions, deals, promotions, giveaways, and relationships with teams and athletes (Fink et al., 2002; Perrault, 2016). Through new applications (apps), athletes and fans are spending more time online (Samet, 2020). These apps allow fans to witness new sides to athletes and teams through increased content which, consequently, helps form connections between fans and athletes (Sharpe et al., 2020). This research analyzed the relationships between teams' and leagues' social media presence on fan behavior by conducting in-depth one-on-one interviews with professionals working in the sports industry at the professional and collegiate levels. A total of eight professionals were interviewed from eight different sports. Questions asked specifically addressed how social media platforms such as Instagram, Facebook, Twitter, and TikTok have affected ticket sales, fan attendance/tune-in rates, engagement, brand loyalty, and merchandise purchases. Using content analysis, best practices were determined for increasing engagement and fan behavior and understanding the relationships crea (open full item for complete abstract)

Committee: Julie Szendrey (Advisor); Nina Rytwinski (Committee Co-Chair); Patricia Berg (Other) Subjects: Marketing; Sports Management

Doctor of Philosophy (Ph.D.), Bowling Green State University, 2021, American Culture Studies

This dissertation analyzes how far-right digitally networked German and American Islamophobic communities on Twitter frame, discuss, and imagine Arab and Muslim communities as supposedly destabilizing the Western-nation state as a racially homogenous national cultural community. Employing a feminist grounded theory methodology this dissertation involves scraping the comparative hashtags #Islamization and #Islamisierung, visualizing digitally networked Islamophobic communities, identifying user-types, analyzing discursive themes, and tracking information transmission to examine the way in which Islamophobic digital discourse is not merely Transatlantic but increasingly transnationalized among American, German, Indian, and Nigerian digital networks. In charting the contours of these Islamophobic digitally networked communities and the content of their conversations, this dissertation tracks the way in which German and American far-right Twitter users increasingly articulate a series of paranoid linkages between Muslim, Jewish, and Black communities alongside political progressives, multi-lateral institutions, and national governments as united in seeking to destabilize an imagined white or ethnic German, Christian, hetero-patriarchal nation-state and the broader cultural imaginary of the West. This dissertation contributes to contemporary studies of far-right digitally networked communities and finds that even as far-right German and American Islamophobic networked communities are mired within racially exclusionary nationalist rhetoric they are increasingly linked to the growth of transnational and multi-racial far-right networks that span the Global North and South.

Committee: Radhika Gajjala Ph.D. (Advisor); Samuel McAbee Ph.D (Other); Yanqin Lu Ph.D. (Committee Member); Timothy Messer-Kruse Ph.D. (Committee Member) Subjects: American Studies; Communication; Ethnic Studies

Bachelor of Arts, Wittenberg University, 2021, Business

This paper analyzes the role of social media in politics through the lens of emotional economic decision-making and hypothesizes that Donald Trump's short and impassioned tweets generate an instant emotional reaction from stockholders stemming from a sustained sense of uncertainty and anxiety about political and economic stability which results in immediate, but short-term, volatility within the stock market. This study categorizes Trump's tweets based on high-level content to analyze whether short-term, intraday change in the S&P 500 responds more significantly to time-lag value indicators or the category of content of Trump's tweets. A series of multiple linear regressions analyzing the relationship between minute-level intraday S&P 500 data and policy-related tweet content categorizations were run with results generally yielding little statistical significance. Despite a lack of substantiated results to support the overarching hypotheses, the prevalence of emotion in economic decision-making cannot be ignored.

Committee: Ed Hasecke (Advisor); Rachel Wilson (Advisor); James Allan (Committee Member); Di Wang (Committee Member) Subjects: Economic Theory; Economics; Finance; Political Science; Technology

Bachelor of Arts, Wittenberg University, 2021, Political Science

The 2019 Mueller Report revealed a campaign by the Russian Internet Research Agency to influence the outcome of the 2016 U.S. presidential election and insert systemic distrust in Western democracy. The campaign engaged in “information warfare” using false accounts, or bots, to prey on inherent social vulnerabilities that are amplified by the novelty and anonymity of social media, such as echo chambers and the rapid spread of fake news. This thesis explores the aims, methods, effects, and behavioral patterns of bots. It also proposes BotWise, a model designed to distill average behavior on the social media platform Twitter from a set of real users and compare that data against novel input.

Committee: Tyler Highlander (Advisor); Staci Rhine (Advisor); Alyssa Hoofnagle (Committee Member); Yu Bin (Committee Member) Subjects: Computer Science; Political Science; Sociology; Technology

BA, Kent State University, 2022, College of Arts and Sciences / Department of Political Science

The world has grown increasingly connected through social media. Despite this, many have been critical of and uncertain of the impacts of social media activism. Many scholars have studied social movements, others have studied social media, but few have combined the data especially in terms of geographic dispersion. In order to assess the role of social media in social movements, this paper analyzes Ferguson as a case study because of its role as a springboard for #BlackLivesMatter. The protests in Ferguson following the shooting of Mike Brown did not create the hashtag, but they did help push the hashtag into mainstream consciousness. I utilized data collected by Ray et al. (2017) in order to visualize the way that tweets about Ferguson expanded across borders and geographic barriers. Overall, many of the tweets looked to be inspiring other tweets due to tweets in isolation blossoming into more and more tweets even without widespread, traditional media coverage.

Committee: Julie Mazzei PhD (Advisor); Suzy D'Enbeau PhD (Committee Member); Charmaine Crawford PhD (Committee Member); Ashley Nickels PhD (Committee Member) Subjects: Mass Media; Political Science; Sociology

Master of Science (MS), Ohio University, 2021, Journalism (Communication)

When a message is sent out to the public what matters most is not only what is said but how it is said along with what is not being said. This process of intentionally highlighting and accentuating certain aspects in a communicating text, while negating the salience of other aspects in order to shape the recipients' understanding of an issue is referred to within the field of communication studies as framing. The most powerful frames are those offered by the president who is considered the highest-ranking member of the political elite in countries with a presidential system like the one in the US. Hence, presidential leadership during a crisis becomes more important and influential than ever. With this in mind, this paper examined what framing patterns dominated Trump's tweeting activity about the COVID-19 pandemic from 24 January, 2020 to 8 January, 2021 with the help of a qualitative content analysis. Trump's tweets were dominated by a cultural populist worldview that is based upon distinguishing between `us' and `them' and eliciting fear from the `others'. The threat of the COVID-19 pandemic was continuously undermined, while public health measures such as lockdown were portrayed through a political lens, as being more harmful than beneficial.

Committee: Jatin Srivastava (Committee Chair) Subjects: Journalism

Doctor of Philosophy (PhD), Ohio University, 2021, Mass Communication (Communication)

This study examines Southern African masculinities in the digital age of #MenAreTrash and #AmINext? This study is a multi-sited digital ethnography which focuses on Twitter and YouTube as field sites. A cyber-womanist framework is used to explore social activism on digital media platforms. The hashtags #MenAreTrash and #AmINext? are concurrent social media campaigns created by women in South Africa to create awareness about gender-based violence. Thus, this study investigates the conceptualization of GBV as articulated by various womxn and men on Twitter and YouTube. The discourse on YouTube includes the documentary film The People vs. Patriarchy and select episodes of The Big Debate. The methodology includes a Thematic Analysis of the audiovisual data and the hashtags related to gender disparities, violence, and femicide. Women are collectively creating a space on social networking sites to critique societal norms and cis-heteronormative cultures. Twitter gives agency to women across Southern Africa as they participate in discussions that center on politics, socio-economic disparities, and violence. This project argues that #MenAreTrash and #AmINext? campaigns as discussed on Twitter and YouTube are resistant measures set as counter-narratives to the normative patriarchal system set in place in South Africa.

Committee: Saumya Pant (Committee Chair); J.W. Smith (Committee Member); Steve Howard (Committee Member); Edna Wangui (Committee Member) Subjects: Mass Communications; Mass Media; Multimedia Communications; Womens Studies

Master of Arts (MA), Ohio University, 2021, Sociology (Arts and Sciences)

Any time a high-profile person transgresses gender norms through dress it calls into question the naturalness of the gender binary, but rappers are a special case due to perceptions of them being hypermasculine which are held by both the general public and their fan bases. Increasingly, African American male rappers have made public appearances wearing items typically associated with female gender roles such as skirts, dresses, and purses. Their choices contradict hypermasculine perceptions of rap artists and have elicited a variety of responses from the public on social media sites. Gender theorists remind us that gender is enacted and re-negotiated through performance and social interaction (West & Zimmerman, 1987; Butler, 1988). Given the performative nature of gender and celebrity status, the transgressive gender performances of male rapper's raise important questions about how people can renegotiate the boundaries of inequalities in the gendered social order. This research study consists of a two-pronged analysis of the content and structure of online conversations where people react to these rapper's gender performances on Twitter as well as an analysis of data collected from Wikipedia. These online conversations document the current and contested state of the gendered social order within the musical genre and in society at large. Initially, the conceptual relationships between different rappers and ideas about gender are examined using social network analysis to visualize the links that are present between the Wikipedia pages of rappers and Wikipedia pages belonging to gender-related terms. Additionally, comparisons within the Wikipedia context reveal how wide-spread understandings of what is relevant to artists may be different based on what was linked to artist's pages. Following insights from this analysis, both content analysis and social network analysis are used to study conversations on Twitter. These conversations relate to specific acts of gender tra (open full item for complete abstract)

Committee: Howard T. Welser (Committee Chair); Anna Rachel Terman (Committee Member); Paula Miller-Buckner (Committee Member) Subjects: Social Research; Social Structure; Sociology