Taraftarların Dijital Geri Bildirimleri Yoluyla Kurumsal İtibar: Antalyaspor Üzerine Bir İnceleme.

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 X (Twitter). The aim of the study is to reveal how the reputation of football clubs is shaped by fan feedback. The data set co...

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Publicado en:Journal of Abant Social Sciences / Abant Sosyal Bilimler Dergisi Vol. 25; no. 1; pp. 294 - 306
Autor principal: YİĞİT AÇIKGÖZ, Fatma
Formato: Artículo
Publicado: Journal of Abant Social Sciences mar2025
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Taraftarların Dijital Geri Bildirimleri Yoluyla Kurumsal İtibar: Antalyaspor Üzerine Bir İnceleme.
      aug:
        au: YİĞİT AÇIKGÖZ, Fatma
        affil: Dr., Fatma Yiğit Açıkgöz, Akdeniz Üniversitesi
      su:
        Social media
        Sentiment analysis
        Python programming language
        Corporate image
        Text mining
      sug:
        subj:
          Social media
          Sentiment analysis
          Python programming language
          Corporate image
          Text mining
      keyword:
        Corporate Reputation
        Sentiment Analysis
        Social Media
        Text Mining
        Antalyaspor
        Duygu Analizi
        Kurumsal İtibar
        Metin Madenciliği
        Sosyal Medya
        Corporate Reputation
        Sentiment Analysis
        Social Media
        Text Mining
        Antalyaspor
        Duygu Analizi
        Kurumsal İtibar
        Metin Madenciliği
        Sosyal Medya
      ab: 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 X (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.
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    language: Turkish
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