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

Li, Xinwei ORCID: https://orcid.org/0000-0002-4796-1189, Tse, Ying Kei and Fastoso, Fernando (2024) Unleashing the power of social media data in business decision making: an exploratory study. Enterprise Information Systems, 18 (1). ISSN 1751-7575

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Abstract

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.

Item Type:	Article
Uncontrolled Keywords:	social media data,business decision-making,systematic literature review,text mining,topic modelling,computer science applications,information systems and management ,/dk/atira/pure/subjectarea/asjc/1700/1706
Faculty \ School:	Faculty of Social Sciences > Norwich Business School
UEA Research Groups:	Faculty of Social Sciences > Research Groups > Innovation, Technology and Operations Management
Related URLs:	http://www.scopus.com/inward/record.url?... https://orca.cardiff.ac.uk/id/eprint/162...
Depositing User:	LivePure Connector
Date Deposited:	04 Mar 2024 18:37
Last Modified:	25 Sep 2024 17:41
URI:	https://ueaeprints.uea.ac.uk/id/eprint/94542
DOI:	10.1080/17517575.2023.2243603

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