11 citations · 29 across the 32 of their papers we have counts for
11 papers · 1 filter
GENDIS: Gender-Related Discourse and Stance in Multilingual YouTube Comments from India, Kenya, and Nigeria
Luise Koch, Manuel Tonneau, Niyati Malhotra +5
Research on gender-related online content is often operationalized through harm-centered tasks that collapse non-harmful gender-related and unrelated content, while existing datase…
LLMs Mirror Country-Specific Gender Patterns If Asked, but Skew Male When Generating Media in Local Languages
Sharif Kazemi, Tanya Popli, Neil K. R. Sehgal +7
Large language models (LLMs) are increasingly used to generate media, but whether their content perpetuates gender stereotypes is unknown: standard benchmarks rely on selection-bas…
Predictors of Loneliness in Older Adults Using Multimodal Analysis of Speech and Language
Vinmay Khandode, Sai Karthik Kosuri, Neil K. R. Sehgal +6
Loneliness is a critical public health issue among older adults, linked to higher risks of depression, cognitive decline, and mortality. Scalable, objective methods for its detecti…
A Concise Agent is Less Expert: Revealing Side Effects of Using Style Features on Conversational Agents
Young-Min Cho, Yuan Yuan, Sharath Chandra Guntuku +1
Style features such as friendly, helpful, or concise are widely used in prompts to steer the behavior of Large Language Model (LLM) conversational agents, yet their unintended side…
Different Demographic Cues Yield Inconsistent Conclusions About LLM Personalization and Bias
Manuel Tonneau, Neil K. R. Sehgal, Niyati Malhotra +7
Demographic cue-based evaluation is widely used to study how large language models (LLMs) adapt their responses to signaled demographic attributes within and across groups. This ap…
Building Knowledge-Guided Lexica to Model Cultural Variation
Shreya Havaldar, Salvatore Giorgi, Sunny Rai +4
Cultural variation exists between nations (e.g., the United States vs. China), but also within regions (e.g., California vs. Texas, Los Angeles vs. San Francisco). Measuring this r…
An Integrative Survey on Mental Health Conversational Agents to Bridge Computer Science and Medical Perspectives
Young Min Cho, Sunny Rai, Lyle Ungar +2
Mental health conversational agents (a.k.a. chatbots) are widely studied for their potential to offer accessible support to those experiencing mental health challenges. Previous su…
Historical patterns of rice farming explain modern-day language use in China and Japan more than modernization and urbanization
Sharath Chandra Guntuku, Thomas Talhelm, Garrick Sherman +4
We used natural language processing to analyze a billion words to study cultural differences on Weibo, one of China's largest social media platforms. We compared predictions from t…
Different Affordances on Facebook and SMS Text Messaging Do Not Impede Generalization of Language-Based Predictive Models
Tingting Liu, Salvatore Giorgi, Xiangyu Tao +4
Adaptive mobile device-based health interventions often use machine learning models trained on non-mobile device data, such as social media text, due to the difficulty and high exp…
Social Media Reveals Urban-Rural Differences in Stress across China
Jesse Cui, Tingdan Zhang, Kokil Jaidka +5
Modeling differential stress expressions in urban and rural regions in China can provide a better understanding of the effects of urbanization on psychological well-being in a coun…
Does Social Support Expressed in Post Titles Elicit Comments in Online Substance Use Recovery Forums?
Anietie Andy, Sharath Guntuku
Individuals recovering from substance use often seek social support (emotional and informational) on online recovery forums, where they can both write and comment on posts, express…