A New Approach to Assess Sustainable Corporate Reputation with Citizen Comments Using Machine Learning and Natural Language Processing

Fatma Yiğit Açikgöz, Mehmet Kayakuş (), Georgiana Moiceanu () and Nesrin Sönmez
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Fatma Yiğit Açikgöz: Department of Marketing and Advertising, Social Sciences Vocational School, Akdeniz University, Antalya 07058, Türkiye
Mehmet Kayakuş: Department of Management Information Systems, Faculty of Social and Human Sciences, Akdeniz University, Antalya 07800, Türkiye
Georgiana Moiceanu: Department of Entrepreneurship and Management, Faculty of Entrepreneurship, Business Engineering and Management, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania
Nesrin Sönmez: Department of Special Education, Faculty of Education, Akdeniz University, 07058 Antalya, Türkiye

Sustainability, 2024, vol. 16, issue 22, 1-19

Abstract: This study investigates the assessment of sustainable corporate reputation through citizen comments and how it can be measured by sentiment analysis methods based on machine learning and text mining. The research analyses citizen feedback on municipalities in the field of public services and examines their impact on the social reputation of the services provided by municipalities. Support vector machines, one of the machine learning methods, was used for sentiment analysis. In the study, Google Maps comments of the citizens receiving services from the municipality were used. The results of the sentiment analysis reveal that sustainable corporate reputation is directly related to citizen satisfaction and feedback. In this context, municipalities should continuously receive feedback and make strategic improvements based on citizens’ comments to ensure sustainable service quality. Municipalities are especially appreciated by citizens for their fast, effective, and high-quality services. However, some negative comments focus on issues such as the slowness of services, cleaning problems, and staff attitudes, indicating that certain improvements are needed. This feedback emphasises the need for continuous improvement in service quality.

Keywords: sustainable reputation; corporate; municipality; machine learning; sentiment analysis; text mining (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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