Yaks versus Tweets: Sentiment Discrepancy During a Social Crisis

dc.contributor.author Koohikamali, Mehrdad
dc.contributor.author Gerhart, Natalie
dc.date.accessioned 2017-12-28T00:53:35Z
dc.date.available 2017-12-28T00:53:35Z
dc.date.issued 2018-01-03
dc.description.abstract People use social networks to get current information, express their emotions and ideas, and connect with others. During a social crisis, there is a heightened value in using a social network to get information. Unfortunately, using a social network during a social crisis also provides fertile grounds for uncertainties and rapid dissemination of misinformation. Currently, there are multiple types of social networks including traditional and anonymous social networks. This research considers the differences between these two types of social networks. During the -˜Concerned Student 1950’, a student activist group at the University of Missouri, crisis at the University of Missouri, we captured users’ messages on two distinct anonymous and traditional social networks. Through sentiment analysis of datasets from Twitter and Yik Yak, we find that people express less total sentiment and more extremity on anonymous social networks. Results show extremity and length positively influence engagement, but total sentiment negatively influence engagement. These findings provide guidance for developers, law enforcement, and social network users.
dc.format.extent 8 pages
dc.identifier.doi 10.24251/HICSS.2018.225
dc.identifier.isbn 978-0-9981331-1-9
dc.identifier.uri http://hdl.handle.net/10125/50112
dc.language.iso eng
dc.relation.ispartof Proceedings of the 51st Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Data Analytics, Data Mining and Machine Learning for Social Media
dc.subject Social media, Anonymity, Social Crisis, Sentiment Analysis
dc.title Yaks versus Tweets: Sentiment Discrepancy During a Social Crisis
dc.type Conference Paper
dc.type.dcmi Text
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