Taraftarların Dijital Geri Bildirimleriyle Kurumsal İtibar: Antalyaspor Üzerine Bir İnceleme

Öz

Bu çalışmada, Antalyaspor’un kurumsal itibarı, sosyal medya platformu Twitter’da taraftarlar tarafından yapılan yorumlar üzerinden yapay zekâ teknikleri kullanılarak incelenmiştir. Çalışmanın amacı, futbol kulüplerinin itibarının taraftar geri bildirimleri ile nasıl şekillendiğini ortaya koymaktır. Veri seti, 2024 yılı Haziran, Temmuz ve Ağustos aylarında Antalyaspor’a yönelik 500 tweetten oluşmaktadır. Bu tweetler, Python programlama dilinde TextBlob kütüphanesi kullanılarak duygu analizine tabi tutulmuştur. Duygular pozitif, negatif ve nötr olarak sınıflandırılmış, ayrıca metin madenciliği yöntemi ile en sık kullanılan kelimeler tespit edilmiştir. Elde edilen bulgular, taraftarların genel olarak kulüp yönetimine duyduğu güveni ve spor başarılarına yönelik olumlu algıyı yansıtmaktadır. Ancak, belirli yönetim kararlarına dair eleştiriler ve transfer politikalarına yönelik memnuniyetsizlikler de bulunmaktadır. Çalışma, sosyal medya geri bildirimlerinin futbol kulüplerinin itibar yönetiminde önemli bir araç olabileceğini göstermektedir.

Anahtar Kelimeler

• Kurumsal İtibar
• Sosyal Medya
• Antalyaspor
• Duygu Analizi
• Metin Madenciliği

Corporate Reputation through Fans' Digital Feedback: A Study on Antalyaspor

Öz

In this study, the corporate reputation of Antalyaspor is analysed by using artificial intelligence techniques through the comments made by fans on the social media platform Twitter. The aim of the study is to reveal how the reputation of football clubs is shaped by fan feedback. The data set consists of 500 tweets about Antalyaspor in June, July, and August 2024. These tweets were subjected to sentiment analysis using the TextBlob library in the Python programming language. Emotions were categorised as positive, negative, and neutral, and the most frequently used words were determined by the text mining method. The findings reflect the fans' general trust in the club management and positive perception of sporting achievements. However, there are also criticisms of certain management decisions and dissatisfaction with transfer policies. The study shows that social media feedback can be an important tool in the reputation management of football clubs.

Anahtar Kelimeler

• Corporate Reputation
• Social Media
• Antalyaspor
• Sentiment Analysis
• Text Mining

Kaynakça

1. Aula, P. (2010). Social Media, Reputation Risk and Ambient Publicity Management. Strategy & Leadership, 38(6), s. 43-49.
2. Baruah, L., Panda, N. M. (2020). Measuring Corporate Reputation: A Comprehensive Model with Enhanced Objectivity. Asia-Pacific Journal of Business Administration, 12(2), s. 139-161.
3. Bee, C. C., Havitz, M. E. (2010). Exploring the Relationship between Involvement, Fan Attraction, Psychological Commitment, and Behavioral Loyalty among Football Fans. Journal of Sport Management, 24(1), s. 1-15.
4. Berens, G., Van Riel, C. B. (2004). Corporate associations in the academic literature: Three main streams of thought in the reputation measurement literature. Corporate reputation review, 7, s. 161-178.
5. Berka, P. (2020). Sentiment Analysis Using Rule-Based and Case-Based Reasoning. Journal of Intelligent Information Systems, 55(1), s. 51-66.
6. Cambria, E., Schuller, B., Xia, Y., Havasi, C. (2013). New Avenues in Opinion Mining and Sentiment Analysis. IEEE Intelligent Systems, 28(2), s. 15-21.
7. Chadwick, S. (2017). The Business of Sport Management. Financial Times/Prentice Hall.
8. Chai, C. P. (2023). Comparison of Text Preprocessing Methods. Natural Language Engineering, 29(3), s. 509- 553.

9. Chandrasekaran, G., Hemanth, J. (2022). Deep Learning and TextBlob Based Sentiment Analysis for Coronavirus (Covid-19) Using Twitter Data. International Journal on Artificial Intelligence Tools, 31(01), 2250011.
10. Christensen, L. T., Morsing, M., Thyssen, O. (2008). The Polyphony of Corporate Social Responsibility: Deconstructing Accountability and Transparency in The Context of Identity and Hypocrisy. Corporate Communications: An International Journal, 13(3), s. 279-293.
11. Chun, R. (2005). Corporate reputation: Meaning and measurement. International Journal of Management Reviews, 7(2), s. 91-109.
12. Coombs, W. T. (2007). Ongoing Crisis Communication: Planning, Managing, and Responding. Sage Publications.
13. Coombs, W. T., Holladay, S. J. (2015). The Handbook of Communication and Corporate Reputation. Wiley- Blackwell.
14. Davies, G. (2003). Corporate Reputation: Understanding Threats and Opportunities. Journal of General Management, 29(2), s. 1-12.
15. Deloitte. (2017). Ahead of the Curve: Annual Review of Football Finance. Sport Business, Deloitte Sport Business Group.
16. Doorley, J., Garcia, H. F. (2020). Reputation Management: The Key to Successful Public Relations and Corporate Communication. Routledge.
17. Fombrun, C., Gardberg, N. (2000). Who’s Tops in Corporate Reputation? Corporate Reputation Review, 3(1), s. 13-17.
18. Fombrun, C., Van Riel, C. B. M. (1997). The Reputational Landscape. Corporate Reputation Review, 1(1), s. 5-13.
19. Fombrun, C. J., Van Riel, C. B. (2004). Fame & Fortune: How Successful Companies Build Winning Reputations. Pearson Education.
20. Haddi, E., Liu, X., Shi, Y. (2013). The Role of Text Pre-Processing in Sentiment Analysis. Procedia computer science, 17, s. 26-32.
21. Gümüş, M., Öksüz, B. (2010). İtibarın Temel Taşı Olarak Kurumsal İletişim: Kurumsal İtibar Sürecinde İletişimin Rolü ve Önemi. Marmara İletişim Dergisi, 16, s. 111-124.
22. Kadhim, A. I. (2018). An Evaluation of Preprocessing Techniques for Text Classification. International Journal of Computer Science and Information Security (IJCSIS), 16(6), s. 22-32.
23. Kayakuş, M., Yiğit Açıkgöz, F. (2022). Classification of News Texts by Categories Using Machine Learning Methods. Alphanumeric Journal, 10(2), s. 155-166.
24. Kayakuş, M., Yiğit Açikgöz, F., Dinca, M. N., Kabas, O. (2024). Sustainable Brand Reputation: Evaluation of iPhone Customer Reviews with Machine Learning and Sentiment Analysis. Sustainability, 16(14), 6121.
25. Lewellyn, P. G. (2002). Corporate reputation: Focusing the Zeitgeist. Business & Society, 41(4), s. 446-455. Mao, R., Li, X., Ge, M., Cambria, E. (2022). MetaPro: A Computational Metaphor Processing Model for Text Pre- Processing. Information Fusion, 86, s. 30-43.
26. Nandwani, P., Verma, R. (2021). A Review on Sentiment Analysis and Emotion Detection from Text. Social network analysis and mining, 11(1), s. 81.
27. Pang, B., Lee, L. (2008). Opinion Mining and Sentiment Analysis. Foundations and Trends® in Information Retrieval, 2(1-2), s. 1-135.
28. Parganas, P., Anagnostopoulos, C., Chadwick, S. (2015). 'You’ll Never Walk Alone’: Brand Associations in The Context of Football Teams’ Corporate Social Responsibility. Journal of Brand Management, 22(7), s. 551-568.
29. Peng, S., Cao, L., Zhou, Y., Ouyang, Z., Yang, A., Li, X., Yu, S. (2022). A Survey on Deep Learning for Textual Emotion Analysis in Social Networks. Digital Communications and Networks, 8(5), s. 745-762.
30. Ponzi, L. J., Fombrun, C. J., Gardberg, N. A. (2011). RepTrak™ Pulse: Conceptualizing and validating a short form measure of corporate reputation. Corporate Reputation Review, 14(1), s. 15-35.
31. Ross, S. D. (2008). Assessing the Use of Brand Associations and Fan Identification to Measure Brand Equity in Sports Teams. International Journal of Sport Management and Marketing, 3(1-2), s. 23-38.
32. Schonlau, M., Guenther, N., Sucholutsky, I. (2017). Text Mining With N-Gram Variables. The Stata Journal, 17(4), s. 866-881.
33. Schwaiger, M. (2004). Components and parameters of corporate reputation: An empirical study. Schmalenbach Business Review, 56, s. 46-71.
34. Tainsky, S., Winfree, J. A. (2010). Building Fan Loyalty through Team Reputation: A Study of the Effect of Winning on Team Popularity. Journal of Sports Economics, 11(5), s. 488-505.
35. Thelwall, M., Buckley, K., Paltoglou, G. (2011). Sentiment in Twitter Events. Journal of the American Society for Information Science and Technology, 62(2), s. 406-418.
36. Thompson, A. J., Martin, A. J., Gee, S., Eagleman, A. N. (2014). Examining the Development of a Social Media Strategy for a National Sport Organization: A Case Study of Tennis New Zealand. Journal of Applied Sport Management, 6(2), s. 14-34.
37. Walters, G., Tacon, R. (2010). Corporate Social Responsibility in Sport: Stakeholder Management in The UK Football Industry. Journal of Management & Organization, 16(4), s. 566-586.
38. Wartick, S. L. (2002). Measuring corporate reputation: Definition and data. Business & Society, 41(4), s. 371-392. Woratschek, H., Schafmeister, G., & Schierl, T. (2007). The Influence of Team Identification and Perceived Team Reputation on the Success of Football Clubs. Sport Marketing Quarterly, 16(2), s. 29-34.
39. Yıldırım, A. (2018). Sporda Halkla İlişkiler: Futbol Kulüplerinde Kriz Yönetimi. Ali Yıldırım.
40. Yiğit Açıkgöz, F., Karakaya, Ç. (2018). Akademik Örgütlerde İtibar Algısı: Akdeniz Üniversite’sinin İç ve Dış Paydaşları Üzerine Bir Araştırma. Akdeniz Üniversitesi İletişim Fakültesi Dergisi, 30, s. 191-217.
41. Zhang, J., Yin, Z., Chen, P., Nichele, S. (2020). Emotion Recognition Using Multi-Modal Data and Machine Learning Techniques: A Tutorial and Review. Information Fusion, 59, s. 103-126.