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

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dc.contributor.authorPilgrim, Katharina
dc.contributor.authorKoss, Jonathan
dc.contributor.authorBohnet-Joschko, Sabine
dc.date.accessioned2022-12-27T19:02:42Z
dc.date.available2022-12-27T19:02:42Z
dc.date.issued2023-01-03
dc.description.abstractAdopting 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.extent10
dc.identifier.doi10.24251/HICSS.2023.268
dc.identifier.isbn978-0-9981331-6-4
dc.identifier.urihttps://hdl.handle.net/10125/102899
dc.language.isoeng
dc.relation.ispartofProceedings of the 56th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectData Analytics, Data Mining, and Machine Learning for Social Media
dc.subjectcsr
dc.subjectnetwork analysis
dc.subjectsocial media mining
dc.subjecttopic model
dc.subjecttwitter
dc.titleCSR Communication on Twitter - A Scoping Review on Social Media Mining and Analytic Methods
dc.type.dcmitext
prism.startingpage2160

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