Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/43067

TitleMeasuring user influence in financial microblogs: experiments using stocktwits data
Author(s)Cortez, Paulo
Oliveira, Nuno Miguel Rocha
Ferreira, João Carlos Peixoto
KeywordsSentiment analysis
Microblogging data
Social networks
User influence
Stock markets
Issue date2016
PublisherACM
CitationIn Proceedings of the 6th International Conference on Web Intelligence, Mining and Semantics (WIMS'16), article no. 17, Nimes, France, June, 2016, ACM, ISBN 978-1-4503-4056-4/16/06 (10 pages).
Abstract(s)In this paper, we study the effect of graph structure user in- fluence measures in financial social media. In particular, we explore rich and recent data, composed of 1.2 million Stock- Twits messages, from June 2010 to March 2013. These data allow the creation of social network graphs by considering direct active interactions (retweets, shares or replies). Using such graphs and a realistic rolling windows evaluation, we analyzed four user influence measures (indegree, between- ness, page rank and posts) under two criteria: Percentage of Quality Users (PQU), as manually labeled by StockTwits; and the daily sentiment correlation between top lists of in- fluential users and other users. The sentiment was based on a StockTwits labeled dataset and assessed in terms of three selections: overall sentiment (ALL) and filtered by two ma- jor technological companies (Apple – AAPL and Google – GOOG). Promising results were obtained, with several top lists pre- senting PQU values higher than 80% and correlations higher than 0.6. Overall, the best results were achieved by the page rank and posts measures.
TypeConference paper
URIhttp://hdl.handle.net/1822/43067
ISBN978-1-4503-4056-4
DOI10.1145/2912845.2912860
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CAlg - Artigos em livros de atas/Papers in proceedings

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