Dec 2, 2019 · This paper automatically creates empathy word ratings from document-level ratings. The underlying problem of learning word ratings from higher-level supervision

We systematically compare a number of approaches to learning word ratings from higher-level supervision against a Mixed-Level Feed Forward Network (MLFFN), ...

This paper systematically compares a number of approaches to learning word ratings from higher-level supervision against a Mixed-Level Feed Forward Network ...

This paper automatically creates empathy word ratings from document-level ratings. The underlying problem of learning word ratings from higher-level supervision ...

May 16, 2020 · Specifically, we learn ratings for two kinds of empathy— empathic concern (feeling for someone) and personal dis- tress (suffering with someone) ...

Learning Word Ratings for Empathy and Distress from Document-Level User Responses. J. Sedoc, S. Buechel, Y. Nachmany, A. Buffone, and L. Ungar.

Learning Word Ratings for Empathy and Distress from Document-Level User Responses ... The underlying problem of learning word ratings from higher-level ...

2017. Learning Word Ratings for Empathy and Distress from Document-Level User Responses. J Sedoc, S Buechel, Y Nachmany, A Buffone, L Ungar. Proceedings of the ...

In this paper, we explore the language of psychological stress with a dataset of 601 social media users, who answered the Perceived Stress Scale questionnaire ...

This contribution presents the first publicly available gold standard for empathy prediction, constructed using a novel annotation methodology which ...