Unleashing the power of social media data in business decision making: an exploratory study

Xinwei Li, Ying Kei Tse, Fernando Fastoso

Research output: Contribution to journalArticlepeer-review


This study systematically reviews the research on applying social media data (SMD) in business decision-making. We applied bibliometric mapping and a Latent Dirichlet Allocation topic modelling approach to conduct a systematic literature review. Results show that research to date has uncovered that sentiment analysis and opinion mining supported businesses in observing, analysing and predicting customer behaviour in various sectors. However, descriptive and predictive analyses are prevalent, while prescriptive analyses on SMD are rare. Our analysis highlights the need for future research to shed light onto newly discovered forms of SMD increasing the accuracy of sentiment detection with concept-level analysis.
Original languageEnglish
Article number2243603
JournalEnterprise Information Systems
Issue number1
Early online date4 Sep 2023
Publication statusPublished - 2024


  • Social media data
  • business decision-making
  • systematic literature review
  • text mining
  • topic modelling

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