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Data science in financial markets: characterization and analysis of stocktwits

Published: 29 October 2019 Publication History

Abstract

Online social networks provide a bunch of useful information that can help to solve different problems. In this context, we present a data characterization and analysis of Stocktwits, a financial online social network, in order to get insights and views that can be applied to financial markets and algorithmic trading (e-commerce). Furthermore, we consider feelings information in messages to create a social indicator, which can be used with a prediction model to support decisions as a strategy for operating in stock markets. Our characterization reveals users behavior and content patterns in the network. Also, our social indicator shows to be useful in the strategy, since it diminished the number of triggers or operations in the market and improved the assertiveness of the model.

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      cover image ACM Other conferences
      WebMedia '19: Proceedings of the 25th Brazillian Symposium on Multimedia and the Web
      October 2019
      537 pages
      ISBN:9781450367639
      DOI:10.1145/3323503
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Publication History

      Published: 29 October 2019

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      Author Tags

      1. data characterization and analysis
      2. data science
      3. e-commerce
      4. financial markets
      5. social networks
      6. stocktwits

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      WebMedia '19
      WebMedia '19: Brazilian Symposium on Multimedia and the Web
      October 29 - November 1, 2019
      Rio de Janeiro, Brazil

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      Overall Acceptance Rate 270 of 873 submissions, 31%

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