Twitter as a predictive system: A systematic literature review

Enrique Cano-Marin, Marçal Mora-Cantallops and Salvador Sánchez-Alonso

Journal of Business Research, 2023, vol. 157, issue C

Abstract: Millions of people use Twitter daily, posting thousands of messages and interacting with their peers. This research aims to evaluate and classify the predictive potential of the Twitter social platform through the intelligent analysis of user-generated public big data analytics. A systematic literature review (SLR) covering Web of Science, IEEE, Scopus and other databases identified the gaps and opportunities for developing predictive applications of User-Generated Content (UGC) on Twitter since 2006. Our research is a practical contribution to the use of Twitter data as a predictive system. A wide variety of application domains, highlighting social network analysis and public health, have been identified by applying innovative techniques for conducting a massive SLR, leveraging machine learning and graph analysis. The results give rise to new research lines with implications for both scholars and business leaders.

Keywords: Systematic literature review; Twitter; Predictive; Research articles; Network analysis; Applications (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:157:y:2023:i:c:s0148296322010268

DOI: 10.1016/j.jbusres.2022.113561

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