A team of researchers has received a $750,000 grant from the NSF’s Convergence Accelerator to study methods of combating misinformation online. Continue reading
New article “Polarization Over Vaccination: Ideological Differences in Twitter Expression About COVID-19 Vaccine Favorability and Specific Hesitancy Concerns” in the journal Social Media + Society from the Center for Communication and Civic Renewal. Continue reading
In the new article “Resonant Moments in Media Events: Discursive Shifts, Agenda Control, and Twitter Dynamics in the First Clinton-Trump Debate” in the Journal of Quantitative Description: Digital Media, the Social Media and Democracy (SMAD) group found key differences in social media discourse about the two candidates during the first 2016 U.S. presidential debate. Continue reading
In the new article “Death Across the News Spectrum: A Time Series Analysis of Partisan Coverage Following Mass Shootings in the U.S.” in the International Journal of Communication, the Social Media and Democracy (SMAD) group analyzed news coverage following mass shooting events. Continue reading
Furthering their research on the #MeToo movement, the Social Media and Democracy (SMAD) team has published “Covering #MeToo across the News Spectrum: Political Accusation and Public Events as Drivers of Press Attention” in The International Journal of Press/Politics. Continue reading
The Social Media and Democracy (SMAD) group has a new article published in New Media & Society. The article, “Performing populism: Trump’s transgressive debate style and the dynamics of Twitter response” was published in April 2020. Continue reading
The Social Media and Democracy (SMAD) group has published a new article in the journal New Media and Society, titled “Trump, Twitter, and news media responsiveness: A media systems approach”. Continue reading
Researchers in the Social Media and Democracy (SMAD) group published their paper, “#MeToo, Networked Acknowledgment, and Connective Action: How Empowerment Through Empathy Launched a Social Movement,” in Social Science Computer Review. The study, led by doctoral candidate Jiyoun Suk, focuses on how sharing #MeToo experiences on Twitter created “a network of acknowledgment” that drove “calls for action” across a range of spaces.
Employing natural language processing and network analysis, the SMAD team analyzed 5-months of Twitter posts following the Weinstein accusations. The research finds that the story sharing and affirmation of “networked acknowledgment” tweets waned over time but “activism” tweets remained relatively robust and even grew over the first few months.
Ordinary users were among the most widely retweeted “networked acknowledgment” accounts. Their prominence demonstrates the grassroots nature of a movement centered on sharing personal narratives and expressing solidarity. For the “activism” discourse, celebrities and media accounts made up a majority of the most retweeted accounts, suggesting elite-driven mobilizing efforts, some directed against politicians facing sexual assault allegations.
Results reveal how major accusations and media events drove these discourses. Time series analysis found (1) these factors didn’t shape “networked acknowledgment” but (2) accusations against politicians did drive “activism.” More important, “networked acknowledgment” discourse drove “activism” discourse, testifying to the potential of personal story sharing to support organizing efforts. The personal became political, with calls to action spurred by the network of support. The team is expanding the project to look at the global spread of #MeToo and the prior hashtag activism that laid the groundwork for it.
Researchers in the Social Media and Democracy (SMAD) group had their paper, “Whose Lives Matter? Mass Shootings and Social Media Discourses of Sympathy and Policy, 2012-2014,” published in the Journal of Computer-Mediated Communication, the highest ranked journal in the field of communications. The study, led by doctoral candidate Yini Zhang, focuses on the outpouring of sympathy in response to mass shootings and the subsequent contestation over gun policy on Twitter from 2012 to 2014 and relates these discourses to features of mass shooting events. The authors use two approaches to Twitter text analysis— hashtag grouping and machine learning—to triangulate an understanding of intensity and duration of “thoughts and prayers,” gun control, and gun rights discourses. Using these data, the authors conducted parallel time series analyses to predict their temporal patterns in response to specific features of mass shootings. Their analyses revealed that while the total number of victims and child deaths consistently predicted public grieving and calls for gun control, public shootings consistently predicted the defense of gun rights. Further, the race of victims and perpetrators affected the levels of public mourning and policy debates, with the loss of black lives and the violence inflicted by white shooters generating less sympathy or policy discourses.
These findings have implications for debates over gun policy. Following the spate of deadly mass shootings in the US in early August, Zhang appeared on Wisconsin Public Television’s Here and Now. She offered insights from this study regarding public response on Twitter after mass shootings, which she explained might contribute to the gun policy impasse. As gun rights discourse on social media persisted more than gun control discourse, and sympathy discourse had an ephemeral life, the signal sent to both journalists and politicians may be that the passion of gun rights supporters merits more attention and action than short-lived appeals for gun control. The team is conducting follow up studies to examine these and other questions.
The research team made up of faculty and graduate students from four UW departments. In addition to Yini Zhang, the other authors on the project include Dhavan Shah, Jordan Foley, Aman Abhishek, Josephine Lukito, Jiyoun Suk, Sang Jung Kim, Zhongkai Sun, Jon Pevehouse, and Christine Garlough. The articles can be downloaded here.
The articles can be downloaded here
A new study by Social Media and Democracy group researchers (link to submission) examines how Trump’s populist communication style, as manifest in his rhetorical and non-verbal approach to Presidential debates, drove reactions on social media. Using detailed verbal, tonal, and visual coding of the first U.S. presidential debate of 2016 between Donald Trump and Hillary Clinton to show how Trump’s transgressive style — i.e., violating normative boundaries, particularly those related to protocol and politeness, and openly displaying anger — can be operationalized from a communication standpoint and related to the “real-time” Twitter responses during the debate. Our findings support the view that Trump’s norm-violating transgressive style, a type of populist political performance, resonated with viewers of the debate who reaction via “second screening.”