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Article: Signal or Noise in Social Media Discussions: The Role of Network Cohesion in Predicting the Bitcoin Market

TitleSignal or Noise in Social Media Discussions: The Role of Network Cohesion in Predicting the Bitcoin Market
Authors
KeywordsSocial media analytics
network cohesion
financial technology
Bitcoin
Fintech
Issue Date2020
PublisherTaylor & Francis Inc. The Journal's web site is located at http://www.tandfonline.com/loi/mmis20
Citation
Journal of Management Information Systems, 2020, v. 37 n. 4, p. 933-956 How to Cite?
AbstractPrior studies have shown that social media discussions can be helpful in predicting price movements in financial markets. With the increasingly large amount of social media data, how to effectively distinguish value-relevant information from noise remains an important question. We study this question by investigating the role of network cohesion in the relationship between social media sentiment and price changes in the Bitcoin market. As network cohesion is associated with information correlation within the discussion network, we hypothesize that less cohesive social media discussion networks are better at predicting the next-day returns than more cohesive networks. Both regression analyses and trading simulations based on data collected from Bitcointalk.org confirm our hypothesis. Our findings enrich the literature on the role of social media in financial markets and provide actionable insights for investors to trade based on social media signals.
Persistent Identifierhttp://hdl.handle.net/10722/294592
ISSN
2020 Impact Factor: 7.838
2020 SCImago Journal Rankings: 3.073
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorXie, P-
dc.contributor.authorChen, H-
dc.contributor.authorHu, YJ-
dc.date.accessioned2020-12-08T07:39:09Z-
dc.date.available2020-12-08T07:39:09Z-
dc.date.issued2020-
dc.identifier.citationJournal of Management Information Systems, 2020, v. 37 n. 4, p. 933-956-
dc.identifier.issn0742-1222-
dc.identifier.urihttp://hdl.handle.net/10722/294592-
dc.description.abstractPrior studies have shown that social media discussions can be helpful in predicting price movements in financial markets. With the increasingly large amount of social media data, how to effectively distinguish value-relevant information from noise remains an important question. We study this question by investigating the role of network cohesion in the relationship between social media sentiment and price changes in the Bitcoin market. As network cohesion is associated with information correlation within the discussion network, we hypothesize that less cohesive social media discussion networks are better at predicting the next-day returns than more cohesive networks. Both regression analyses and trading simulations based on data collected from Bitcointalk.org confirm our hypothesis. Our findings enrich the literature on the role of social media in financial markets and provide actionable insights for investors to trade based on social media signals.-
dc.languageeng-
dc.publisherTaylor & Francis Inc. The Journal's web site is located at http://www.tandfonline.com/loi/mmis20-
dc.relation.ispartofJournal of Management Information Systems-
dc.subjectSocial media analytics-
dc.subjectnetwork cohesion-
dc.subjectfinancial technology-
dc.subjectBitcoin-
dc.subjectFintech-
dc.titleSignal or Noise in Social Media Discussions: The Role of Network Cohesion in Predicting the Bitcoin Market-
dc.typeArticle-
dc.identifier.emailChen, H: chen19@hku.hk-
dc.identifier.authorityChen, H=rp02520-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/07421222.2020.1831762-
dc.identifier.hkuros320570-
dc.identifier.volume37-
dc.identifier.issue4-
dc.identifier.spage933-
dc.identifier.epage956-
dc.identifier.isiWOS:000594446200003-
dc.publisher.placeUnited States-

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