AAAI Publications, The Thirtieth International Flairs Conference

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“Hang In There:" Lexical and Visual Analysis to Identify Posts Warranting Empathetic Responses
Mimansa Jaiswal, Sairam Tabibu, Erik Cambria

Last modified: 2017-05-03

Abstract


In the past few years, social media has risen as a platform where people express and share personal incidences about abuse, violence and mental health issues. There is a need to pinpoint such posts and learn the kind of response expected. For this purpose, we understand the sentiment that a personal story elicits on different posts present on different social media sites, on the topics of abuse or mental health. In this paper, we propose a method supported by hand-crafted features to judge if the post requires an empathetic response. The model is trained upon posts from various web-pages and corresponding comments, on both the captions and the images. We were able to obtain 80% accuracy in tagging posts requiring empathetic responses.

Keywords


empathy; natural language; vision; multimodal

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