Hashing it Out: Racial Conversations and Harassment on Social Media
Restricted (Penn State Only)
- Author:
- Francisco, Sara Chari
- Graduate Program:
- Sociology
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- April 29, 2022
- Committee Members:
- Ashton Verdery, Major Field Member
Burt Monroe, Outside Unit & Field Member
Diane Felmlee, Chair & Dissertation Advisor
David Baker, Professor in Charge/Director of Graduate Studies
Melissa Hardy, Major Field Member
Kevin J Thomas, Special Member
Kevin Thomas, Special Member - Keywords:
- Social Media
Social Networks
Race
Gender
Cyberbullying
Black Lives Matter - Abstract:
- This dissertation contributes to the study of racism and sexism by highlighting the communications that are taking place within online settings. For my dissertation research, I study interactions related to race within the social media platform, Twitter. In doing so, I examine attitudes and commentaries within two different contexts. The first is within one of the largest racial social movements, Black Lives Matter, and its counter movements during 2014 and 2020. The second concerns daily interactions and harassment toward Black and Latinx women. My dissertation contributes to the theoretical and empirical study of racial attitudes on Twitter and furthers a better understanding of the social processes involved in racial and political conversations on social media. Using big data, and in particular, public messages from Twitter, I study attitudes toward current issues related to race and consider how individuals communicate, react, and engage in conversations about racial inequality. In my first empirical chapter, I examine the thematic content contained in messages related to Blacks, police brutality, and the Ferguson protests stemming from the Black Lives Matter movement, its counter-movements, on the social media platform, Twitter. I utilize a statistical, text clustering method, topic modeling by Latent Dirichlet Allocation, to identify common subjects and word patterns that arise in tweets. I ask two questions. First, what is the thematic content of the tweets related to these social movements? Second, to what extent does the content reflect racist stereotypes? Based on my findings from the topic modelling, five themes emerged within my data, such as the “militarization of police.” I also uncover several derogatory stereotypes toward Blacks within messages about the Ferguson protests and BLM. For instance, the stereotype of the “scary thug” occurred frequently in my data. Overall, these types of stereotypes demonstrate how society uses a combination of race, social class, and socioeconomic status in shaping demeaning labels for Black individuals. The second analysis chapter focuses on both the BLM movement during 2014 and 2020. I apply a social network analysis approach to explore hashtag usage within the online movement and its counter movements. I argue that there is a shift in discussion between 2014 and 2020, and that these changes are evident in the hashtags used within tweets. I amassed over 4 million tweets, and analyzed a wide range of hashtags used during the two movements. I found that the emergence and popularity of two counter movements, Blue Lives Matter and All Lives Matter, have grown substantially since 2014. In contrast to 2014, more hashtags in 2020 related to the movement increased and sought accountability for police behavior. Interestingly, the counter movements and their hashtags were most often in response to the Black Lives Matter movement, which suggests that the original movement gained more support and popularity since 2014. Furthermore, locations and names were prevalent in Twitter activity during both two time periods, and were some of the first hashtags to go viral in both waves. As shown, the increased reactions from the counter movements, such as All Lives Matter, in response to more support for the Black Lives Matter (BLM) movement deflects and diminishes the stated goals of BLM. Finally, my findings also illustrate the relevance of racial conflict theories. The online interactions that I uncover and visualize between BLM and the counter movement Blue Lives Matter reflect the serious conflict that arises between struggles for racial justice and societal structures/institutions. In the third empirical chapter, I examine online harassment directed towards women of color. I apply a social network analyses and topic modelling to messages posted on the social media platform Twitter. In doing so, I study the occurrence of aggressive, harmful Twitter messages directed towards two groups - Hispanic/Latinx women and Black women. I found common themes emerged within daily online interactions. Messages towards both groups of women contained themes of racial stereotypes. In tweets that targeted Black women, one emergent theme concerned charges of promiscuity, where messages included slurs that accused Black women of being overly sexual. In messages containing Latinx slurs, on the other hand, xenophobia was one frequent topic, with common terms related to menial labor and political comments invoking the need to “build a wall.” Both groups of women also were subjected to feminine, attractiveness insults, demonstrating intersectional, race and gender themes that emerged in the data. These findings suggest that these negative communications are not idiosyncratic in nature, but instead routinely reinforce traditional, negative, race and gender stereotypes. As a result, these hostile messages contribute to the maintenance of race and gender inequality. Overall, this dissertation contributes to the study of anti-racism, while highlighting the ways in which racial minorities can be attacked within online communication. One of the main goals of this research was to raise awareness of racial conversations taking place within online spaces. In doing so, I identify some of the racial conflict occurring on social media. While I find numerous instances of harmful interactions regarding race, gender and class, I also discover that there are positive interactions that show the promise, and allure, of social media.