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Corporate Disclosure via Social Media: A Data Science Approach
Faculty of Management Technology, German University in Cairo, Cairo, Egypt.
Faculty of Management Technology, German University in Cairo, Cairo, Egypt.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Digital Services and Systems. (Information Systems)ORCID iD: 0000-0003-4250-4752
2020 (English)In: Online information review (Print), ISSN 1468-4527, E-ISSN 1468-4535, Vol. 44, no 1, p. 278-298Article in journal (Refereed) Published
Abstract [en]

Purpose - The aim of this paper is to investigate corporate financial disclosure via Twitter among the top listed 350 companies in the UK as well as identify the determinants of the extent of social media usage to disclose financial information.

Design/methodology/approach – This study applies an unsupervised machine learning technique, namely, Latent Dirichlet Allocation (LDA) topic modeling to identify financial disclosure tweets. Panel, Logistic, and Generalized Linear Model Regressions are also run to identify the determinants of financial disclosure on Twitter focusing mainly on board characteristics.

Findings – Topic modeling results reveal that companies mainly tweet about 12 topics, including financial disclosure, which has a probability of occurrence of about 7 percent. Several board characteristics are found to be associated with the extent of Twitter usage as a financial disclosure platform, among which are board independence, gender diversity, and board tenure.

Originality/value – Extensive literature examines disclosure via traditional media and its determinants, yet this paper extends the literature by investigating the relatively new disclosure channel of social media. This study is among the first to utilize machine learning, instead of manual coding techniques, to automatically unveil the tweets’ topics and reveal financial disclosure tweets. It is also among the first to investigate the relationships between several board characteristics and financial disclosure on Twitter; providing a distinction between the roles of executive versus non-executive directors relating to disclosure decisions.

Place, publisher, year, edition, pages
Emerald Group Publishing Limited, 2020. Vol. 44, no 1, p. 278-298
Keywords [en]
Social Media, Topic Modeling, Corporate Disclosure, Board Structure, LDA
National Category
Computer Systems Information Systems, Social aspects
Research subject
Information systems
Identifiers
URN: urn:nbn:se:ltu:diva-77094DOI: 10.1108/OIR-03-2019-0084ISI: 000506710800001OAI: oai:DiVA.org:ltu-77094DiVA, id: diva2:1376107
Note

Validerad;2020;Nivå 2;2020-03-05 (johcin)

Available from: 2019-12-08 Created: 2019-12-08 Last updated: 2020-03-05Bibliographically approved

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Elragal, Ahmed

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