Modeling Empathy and Distress in Reaction to News Stories
Table 1: Illustrative examples from our newly created gold standard with ratings for empathy (E) and distress (D).
['[EMPTY]', '[BOLD] E', '[BOLD] D', '[BOLD] Message']
The participant in Example (1) displays higher empathy than distress, (2) displays higher distress than empathy, and (3) shows neither empathic state, but employs sarcasm, colloquialisms and social-media-style acronyms to express lack of emotional response to the article. As can be seen, the language of our corpus is diverse and authentic, featuring many phenomena of natural language which render its computational understanding difficult, thus constituting a sound but challenging gold standard for empathy prediction.