Analyzing market performance via social media: A case study of a banking industry crisis

Cui Qing Jiang, Kun Liang, Hsinchun Chen, Yong Ding

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


Analyzing market performance via social media has attracted a great deal of attention in the finance and machine- learning disciplines. However, the vast majority of research does not consider the enormous influence a crisis has on social media that further affects the relationship between social media and the stock market. This article aims to address these challenges by proposing a multistage dynamic analysis framework. In this framework, we use an authorship analysis technique and topic model method to identify stakeholder groups and topics related to a special firm. We analyze the activities of stakeholder groups and topics in different periods of a crisis to evaluate the crisis's influence on various social media parameters. Then, we construct a stock regression model in each stage of crisis to analyze the relationships of changes among stakeholder groups/topics and stock behavior during a crisis. Finally, we discuss some interesting and significant results, which show that a crisis affects social media discussion topics and that different stakeholder groups/topics have distinct effects on stock market predictions during each stage of a crisis.

Original languageEnglish (US)
Pages (from-to)1-18
Number of pages18
JournalScience China Information Sciences
Issue number5
StatePublished - May 2014


  • authorship analysis technique
  • market performance
  • social media
  • stakeholder theory
  • topic model

ASJC Scopus subject areas

  • Computer Science(all)


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