4 citations · 51 across the 43 of their papers we have counts for
45 papers
AI Agents are Vulnerable to Radicalization
Ozgur Can Seckin, Shalmoli Ghosh, Alessandro Flammini +3
Large language models (LLMs) can influence people's beliefs, yet little is known about whether and how they can manipulate each other. To investigate this, we simulate conversation…
Characterizing Network Structure of Anti-Trans Actors on TikTok
Maxyn Leitner, Rebecca Dorn, Fred Morstatter +1
The recent proliferation of short form video social media sites such as TikTok has been effectively utilized for increased visibility, communication, and community connection among…
Estimating Causal Effects of Text Interventions Leveraging LLMs
Siyi Guo, Myrl G. Marmarelis, Fred Morstatter +1
Quantifying the effects of textual interventions in social systems, such as reducing anger in social media posts to see its impact on engagement, is challenging. Real-world interve…
Improving and Assessing the Fidelity of Large Language Models Alignment to Online Communities
Minh Duc Chu, Zihao He, Rebecca Dorn +1
Large language models (LLMs) have shown promise in representing individuals and communities, offering new ways to study complex social dynamics. However, effectively aligning LLMs…
Leveraging Machine Learning to Identify Gendered Stereotypes and Body Image Concerns on Diet and Fitness Online Forums
Minh Duc Chu, Cinthia Sánchez, Zihao He +3
The pervasive expectations about ideal body types in Western society can lead to body image concerns, dissatisfaction, and in extreme cases, eating disorders and other psychopathol…
Harmful Speech Detection by Language Models Exhibits Gender-Queer Dialect Bias
Rebecca Dorn, Lee Kezar, Fred Morstatter +1
Content moderation on social media platforms shapes the dynamics of online discourse, influencing whose voices are amplified and whose are suppressed. Recent studies have raised co…
COMMUNITY-CROSS-INSTRUCT: Unsupervised Instruction Generation for Aligning Large Language Models to Online Communities
Zihao He, Minh Duc Chu, Rebecca Dorn +2
Social scientists use surveys to probe the opinions and beliefs of populations, but these methods are slow, costly, and prone to biases. Recent advances in large language models (L…
Don't Blame the Data, Blame the Model: Understanding Noise and Bias When Learning from Subjective Annotations
Abhishek Anand, Negar Mokhberian, Prathyusha Naresh Kumar +5
Researchers have raised awareness about the harms of aggregating labels especially in subjective tasks that naturally contain disagreements among human annotators. In this work we…
GET-Tok: A GenAI-Enriched Multimodal TikTok Dataset Documenting the 2022 Attempted Coup in Peru
Gabriela Pinto, Keith Burghardt, Kristina Lerman +1
TikTok is one of the largest and fastest-growing social media sites in the world. TikTok features, however, such as voice transcripts, are often missing and other important feature…
Reading Between the Tweets: Deciphering Ideological Stances of Interconnected Mixed-Ideology Communities
Zihao He, Ashwin Rao, Siyi Guo +2
Recent advances in NLP have improved our ability to understand the nuanced worldviews of online communities. Existing research focused on probing ideological stances treats liberal…
How Susceptible are Large Language Models to Ideological Manipulation?
Kai Chen, Zihao He, Jun Yan +2
Large Language Models (LLMs) possess the potential to exert substantial influence on public perceptions and interactions with information. This raises concerns about the societal i…
Whose Emotions and Moral Sentiments Do Language Models Reflect?
Zihao He, Siyi Guo, Ashwin Rao +1
Language models (LMs) are known to represent the perspectives of some social groups better than others, which may impact their performance, especially on subjective tasks such as c…
The Pulse of Mood Online: Unveiling Emotional Reactions in a Dynamic Social Media Landscape
Siyi Guo, Zihao He, Ashwin Rao +3
The rich and dynamic information environment of social media provides researchers, policy makers, and entrepreneurs with opportunities to learn about social phenomena in a timely m…
Large Language Models Help Reveal Unhealthy Diet and Body Concerns in Online Eating Disorders Communities
Minh Duc Chu, Zihao He, Rebecca Dorn +1
Eating disorders (ED), a severe mental health condition with high rates of mortality and morbidity, affect millions of people globally, especially adolescents. The proliferation of…
IsamasRed: A Public Dataset Tracking Reddit Discussions on Israel-Hamas Conflict
Kai Chen, Zihao He, Keith Burghardt +2
The conflict between Israel and Palestinians significantly escalated after the October 7, 2023 Hamas attack, capturing global attention. To understand the public discourse on this…
Inducing Political Bias Allows Language Models Anticipate Partisan Reactions to Controversies
Zihao He, Siyi Guo, Ashwin Rao +1
Social media platforms are rife with politically charged discussions. Therefore, accurately deciphering and predicting partisan biases using Large Language Models (LLMs) is increas…
Capturing Perspectives of Crowdsourced Annotators in Subjective Learning Tasks
Negar Mokhberian, Myrl G. Marmarelis, Frederic R. Hopp +3
Supervised classification heavily depends on datasets annotated by humans. However, in subjective tasks such as toxicity classification, these annotations often exhibit low agreeme…
Affective Polarization and Dynamics of Information Spread in Online Networks
Kristina Lerman, Dan Feldman, Zihao He +1
Members of different political groups not only disagree about issues but also dislike and distrust each other. While social media can amplify this emotional divide -- called affect…
Discovering collective narratives shifts in online discussions
Wanying Zhao, Siyi Guo, Kristina Lerman +1
Narrative is a foundation of human cognition and decision making. Because narratives play a crucial role in societal discourses and spread of misinformation and because of the perv…
Measuring Online Emotional Reactions to Events
Siyi Guo, Zihao He, Ashwin Rao +5
The rich and dynamic information environment of social media provides researchers, policy makers, and entrepreneurs with opportunities to learn about social phenomena in a timely m…
Socio-Linguistic Characteristics of Coordinated Inauthentic Accounts
Keith Burghardt, Ashwin Rao, Siyi Guo +6
Online manipulation is a pressing concern for democracies, but the actions and strategies of coordinated inauthentic accounts, which have been used to interfere in elections, are n…
Pandemic Culture Wars: Partisan Differences in the Moral Language of COVID-19 Discussions
Ashwin Rao, Siyi Guo, Sze-Yuh Nina Wang +2
Effective response to pandemics requires coordinated adoption of mitigation measures, like masking and quarantines, to curb a virus's spread. However, as the COVID-19 pandemic demo…
Radicalized by Thinness: Using a Model of Radicalization to Understand Pro-Anorexia Communities on Twitter
Kristina Lerman, Aryan Karnati, Shuchan Zhou +5
The rise in eating disorders, a condition with serious health complications, has been linked to the proliferation of idealized body images on social media platforms. However, the r…
CPL-NoViD: Context-Aware Prompt-based Learning for Norm Violation Detection in Online Communities
Zihao He, Jonathan May, Kristina Lerman
Detecting norm violations in online communities is critical to maintaining healthy and safe spaces for online discussions. Existing machine learning approaches often struggle to ad…