24 citations · 36 across the 4 of their papers we have counts for
5 papers · 1 filter
Empathic Conversations: A Multi-level Dataset of Contextualized Conversations
Damilola Omitaomu, Shabnam Tafreshi, Tingting Liu +5
Empathy is a cognitive and emotional reaction to an observed situation of others. Empathy has recently attracted interest because it has numerous applications in psychology and AI,…
Regional Negative Bias in Word Embeddings Predicts Racial Animus--but only via Name Frequency
Austin van Loon, Salvatore Giorgi, Robb Willer +1
The word embedding association test (WEAT) is an important method for measuring linguistic biases against social groups such as ethnic minorities in large text corpora. It does so…
World Trade Center responders in their own words: Predicting PTSD symptom trajectories with AI-based language analyses of interviews
Youngseo Son, Sean A. P. Clouston, Roman Kotov +4
Background: Oral histories from 9/11 responders to the World Trade Center (WTC) attacks provide rich narratives about distress and resilience. Artificial Intelligence (AI) models p…
Detecting Emerging Symptoms of COVID-19 using Context-based Twitter Embeddings
Roshan Santosh, H. Andrew Schwartz, Johannes C. Eichstaedt +2
In this paper, we present an iterative graph-based approach for the detection of symptoms of COVID-19, the pathology of which seems to be evolving. More generally, the method can b…
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…