On the influence of emotional valence shifts on the spread of information in social networks

Ema Kušen, Mark Strembeck, Giuseppe Cascavilla, Mauro Conti

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

22 Citations (Scopus)

Abstract

In this paper, we present a study on 4.4 million Twitter messages related to 24 systematically chosen real-world events. For each of the 4.4 million tweets, we first extracted sentiment scores based on the eight basic emotions according to Plutchik’s wheel of emotions. Subsequently, we investigated the effects of shifts in the emotional valence on the spread of information. We found that in general OSN users tend to conform to the emotional valence of the respective real-world event. However, we also found empirical evidence that prospectively negative real-world events exhibit a significant amount of shifted emotions in the corresponding tweets (i.e. positive messages). To explain this finding, we use the theory of social connection and emotional contagion. To the best of our knowledge, this is the first study that provides empirical evidence for the undoing hypothesis in online social networks (OSNs). The undoing hypothesis postulates that positive emotions serve as an antidote during negative events.

Original languageEnglish
Title of host publicationProceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017
EditorsJana Diesner, Elena Ferrari, Guandong Xu
PublisherAssociation for Computing Machinery
Pages321-324
Number of pages4
ISBN (Electronic)9781450349932
DOIs
Publication statusPublished - 31 Jul 2017
Event9th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017 - Sydney, Australia
Duration: 31 Jul 20173 Aug 2017

Publication series

NameProceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017

Conference

Conference9th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017
Country/TerritoryAustralia
CitySydney
Period31/07/173/08/17

Keywords

  • Diffusion
  • Sentiment analysis
  • Twitter

Fingerprint

Dive into the research topics of 'On the influence of emotional valence shifts on the spread of information in social networks'. Together they form a unique fingerprint.

Cite this