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Title: Application of data mining techniques to stakeholder sentiment analysis towards corporate social responsibility in the social media: a case study on S&P 500 firms

Authors: Markus Stiglbauer; Christian Häußinger

Addresses: School of Business and Economics, University of Erlangen-Nürnberg, Lange Gasse 20, 90403 Nuremberg, Germany ' School of Business and Economics, University of Erlangen-Nürnberg, Lange Gasse 20, 90403 Nuremberg, Germany

Abstract: The issue of corporate social responsibility (CSR) and the use of social media have increased in importance over the last few years. Companies are not judged solely on their economic performance because they also have to succeed ecologically and socially. Social media (e.g., Facebook, Twitter, and Google Alerts) exert pressure on companies to meet the expectations of different stakeholders in terms of their CSR. Thus, social media are a useful resource for companies who want to ensure that their CSR self-image matches their CSR public image. Data mining techniques and related software (e.g., RapidMiner) can help companies evaluate their CSR public image and adjust their CSR if there is a mismatch between their self-image and public image. Thus, there may be a continuous CSR (control) cycle that helps companies to gain a long-term competitive advantage over companies who do not manage their CSR strategically.

Keywords: data mining; social media; corporate social responsibility; CSR; stakeholder management; Facebook; Google Alerts; Yahoo! Pipes; RapidMiner; web science; self-image; public image; sentiment analysis; corporate image.

DOI: 10.1504/IJWS.2013.056573

International Journal of Web Science, 2013 Vol.2 No.1/2, pp.27 - 43

Available online: 25 Sep 2013 *

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