Affiliation:
1. Pennsylvania State University, USA
Abstract
Emotions are non-negligible parts of the experience among the cancer-affected population to be reckoned with. With the increasing usage of social media platforms as venues for emotional disclosure, we ask the question, what and how are the emotions of the cancer community being shared there? Using a deep learning model and social network analysis, we investigated emotions expressed in a large collection of cancer-related tweets. The results showed that joy was the most commonly shared emotion, followed by sadness and fear, with anger, hope, and bittersweet being less shared. In addition, both the gatekeepers and influencers were more likely to post content with positive emotions, while gatekeepers refrained themselves from posting negative emotions to a greater extent. Last, cancer-related tweets with joy, sadness, and hope received more likes, whereas tweets with joy and anger were more retweeted. The implications of the findings are discussed in the context of social media health communities.
Subject
Computer Science Applications,Communication,Cultural Studies
Cited by
33 articles.
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