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Sentiment and Deep Learning Content Analysis of a Digital Fan Token Platform: An Exploratory Study

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Research and Innovation Forum 2023 (RIIFORUM 2023)

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Abstract

This study aims to investigate the emerging factors of using a digital platform for sport fan Engagement enhanced by new technologies. The study employs a theoretical framework encompassing uses and gratification theory (U&G) drivers of digital platform usage. A total of 1048 English-language reviews were extracted from the main marketplaces and a sentiment analysis and content analysis were conducted using an LDA deep learning model. The results revealed five key factors for fan engagement in this digital community: security, entertainment, customer service, user experience and finances which are interrelated with those found in the literature. This research contributes to the existing body of knowledge by examining the drivers of fan engagement in the context of fan token platforms, with implications for both academics and practitioners in the sports industry, since these results can inform the development of effective marketing and communication strategies that address the interests and needs of sports fans.

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Authors and Affiliations

  1. University of Salerno, 84084, Fisciano, Italy

    Giovanni Baldi, Antonio Botti & Luca Carrubbo

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  1. Giovanni Baldi
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  2. Antonio Botti
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  3. Luca Carrubbo
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Correspondence to Giovanni Baldi .

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Editors and Affiliations

  1. SGH Warsaw School of Economics, Warsaw, Poland

    Anna Visvizi

  2. Università degli Studi di Salerno, Fisciano, Italy

    Orlando Troisi

  3. University of Messina, Messina, Italy

    Vincenzo Corvello

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Baldi, G., Botti, A., Carrubbo, L. (2024). Sentiment and Deep Learning Content Analysis of a Digital Fan Token Platform: An Exploratory Study. In: Visvizi, A., Troisi, O., Corvello, V. (eds) Research and Innovation Forum 2023. RIIFORUM 2023. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-031-44721-1_40

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