CSR Communication on Twitter - A Scoping Review on Social Media Mining and Analytic Methods

dc.contributor.author Pilgrim, Katharina
dc.contributor.author Koss, Jonathan
dc.contributor.author Bohnet-Joschko, Sabine
dc.date.accessioned 2022-12-27T19:02:42Z
dc.date.available 2022-12-27T19:02:42Z
dc.date.issued 2023-01-03
dc.description.abstract Adopting corporate social responsibility (CSR) is becoming increasingly mandatory as international legislation puts pressure on companies to implement and report on appropriate CSR measures. As of 2024, a significant number of companies will need to report on CSR topics for the first time. To identify relevant topics that resonate best in the industry or even with one's own stakeholder groups and should therefore be picked up, addressed and reported on preferentially, social media mining (SMM) can be an efficient ap-proach for companies. By reviewing applied SMM and analytic methods of Twitter data, we identified four methodological approaches that use algorithms to identify relevant CSR topics for companies to engage with. This scoping review thus provides a systematized overview of SMM pipelines for use, being equally relevant for academics and practitioners aiming at computational analysis of Twitter content regarding CSR activities and communication.
dc.format.extent 10
dc.identifier.doi 10.24251/HICSS.2023.268
dc.identifier.isbn 978-0-9981331-6-4
dc.identifier.uri https://hdl.handle.net/10125/102899
dc.language.iso eng
dc.relation.ispartof Proceedings of the 56th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Data Analytics, Data Mining, and Machine Learning for Social Media
dc.subject csr
dc.subject network analysis
dc.subject social media mining
dc.subject topic model
dc.subject twitter
dc.title CSR Communication on Twitter - A Scoping Review on Social Media Mining and Analytic Methods
dc.type.dcmi text
prism.startingpage 2160
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