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Negative emotions shape the diffusion of cancer tweets: toward an integrated social network–text analytics approach

Negative emotions shape the diffusion of cancer tweets: toward an integrated social network–text... Drawing on the cognitive-functional model of emotions and emotional contagion, the authors aim to examine the role of negative emotions in the diffusion of cancer tweets.Design/methodology/approachUsing an integrated approach of social network and text analytics, the authors analyzed 142,883 cancer tweets from February to March 2018. The roles of negative emotions, emotional contagion, cancer themes and user influence on the diffusion of cancer tweets were examined.FindingsResults indicated that cancer tweets expressing negativity and anger diffused more widely, while those expressing sadness or fear were less likely to diffuse. However, contrary to the authors’ expectation, cancer tweets expressing negative emotions (i.e. negativity, anger and fear) were less likely to arouse similar emotions among retweets, thus suggesting that emotions in cancer tweets were not as contagious as they seemed. Finally, user influence was the most important factor explaining the diffusion of cancer tweets, although cancer-related themes (i.e. affective, informative and social) had marginal effects on likelihood of diffusion.Originality/valueUsing a novel integrated social network–text analytics approach, the authors found that to understand cancer tweets' diffusion, it is critical to go beyond examining the content of tweets about cancer and the influence of messengers – the virality of cancer tweets is inextricable from the negative emotions. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Internet Research Emerald Publishing

Negative emotions shape the diffusion of cancer tweets: toward an integrated social network–text analytics approach

Wang, Xiaohui; Lee, Edmund W.J.
Internet Research , Volume 31 (2): 18 – Mar 10, 2021
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References (72)

Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
1066-2243
DOI
10.1108/intr-04-2020-0181
Publisher site
See Article on Publisher Site

Abstract

Drawing on the cognitive-functional model of emotions and emotional contagion, the authors aim to examine the role of negative emotions in the diffusion of cancer tweets.Design/methodology/approachUsing an integrated approach of social network and text analytics, the authors analyzed 142,883 cancer tweets from February to March 2018. The roles of negative emotions, emotional contagion, cancer themes and user influence on the diffusion of cancer tweets were examined.FindingsResults indicated that cancer tweets expressing negativity and anger diffused more widely, while those expressing sadness or fear were less likely to diffuse. However, contrary to the authors’ expectation, cancer tweets expressing negative emotions (i.e. negativity, anger and fear) were less likely to arouse similar emotions among retweets, thus suggesting that emotions in cancer tweets were not as contagious as they seemed. Finally, user influence was the most important factor explaining the diffusion of cancer tweets, although cancer-related themes (i.e. affective, informative and social) had marginal effects on likelihood of diffusion.Originality/valueUsing a novel integrated social network–text analytics approach, the authors found that to understand cancer tweets' diffusion, it is critical to go beyond examining the content of tweets about cancer and the influence of messengers – the virality of cancer tweets is inextricable from the negative emotions.

Journal

Internet Research – Emerald Publishing

Published: Mar 10, 2021

Keywords: Negative emotions; Cancer; Information diffusion; Text analytics; Social network analysis; Big data

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