9 citations · 9 across the 1 of their papers we have counts for
6 papers
Quantifying Community Characteristics of Maternal Mortality Using Social Media
Rediet Abebe, Salvatore Giorgi, Anna Tedijanto +2
While most mortality rates have decreased in the US, maternal mortality has increased and is among the highest of any OECD nation. Extensive public health research is ongoing to be…
Learning Word Ratings for Empathy and Distress from Document-Level User Responses
João Sedoc, Sven Buechel, Yehonathan Nachmany +2
Despite the excellent performance of black box approaches to modeling sentiment and emotion, lexica (sets of informative words and associated weights) that characterize different e…
Understanding and Measuring Psychological Stress using Social Media
Sharath Chandra Guntuku, Anneke Buffone, Kokil Jaidka +2
A body of literature has demonstrated that users' mental health conditions, such as depression and anxiety, can be predicted from their social media language. There is still a gap…
Modeling Empathy and Distress in Reaction to News Stories
Sven Buechel, Anneke Buffone, Barry Slaff +2
Computational detection and understanding of empathy is an important factor in advancing human-computer interaction. Yet to date, text-based empathy prediction has the following ma…
The Remarkable Benefit of User-Level Aggregation for Lexical-based Population-Level Predictions
Salvatore Giorgi, Daniel Preotiuc-Pietro, Anneke Buffone +3
Nowcasting based on social media text promises to provide unobtrusive and near real-time predictions of community-level outcomes. These outcomes are typically regarding people, but…
Predicting Human Trustfulness from Facebook Language
Mohammadzaman Zamani, Anneke Buffone, H. Andrew Schwartz
Trustfulness -- one's general tendency to have confidence in unknown people or situations -- predicts many important real-world outcomes such as mental health and likelihood to coo…