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Clubhouse Experience: Sentiment Analysis of an Alternative Platform From the Eyes of Classic Social Media Users
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Author(s): Ipek Deveci Kocakoç (Dokuz Eylul University, Turkey)and Pınar Özkan (Dokuz Eylul University, Turkey)
Copyright: 2022
Pages: 21
Source title:
Data Mining Approaches for Big Data and Sentiment Analysis in Social Media
Source Author(s)/Editor(s): Brij B. Gupta (National Institute of Technology, Kurukshetra, India), Dragan Peraković (University of Zagreb, Croatia), Ahmed A. Abd El-Latif (Menoufia University, Egypt & Prince Sultan University, Saudi Arabia)and Deepak Gupta (LoginRadius Inc., Canada)
DOI: 10.4018/978-1-7998-8413-2.ch011
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Abstract
Clubhouse is an invitation-only social networking application that differs from the usual social media platforms in that it is “audio only.” In this chapter, the sentiments in the social media messages about Clubhouse in the classic SMPs are examined by supervised learning (by using Hugging Face Transformer Library), and the user feelings are analyzed. Because Turkey is in the first ranks among European countries in terms of both the number of social media users and the number of messages, the analysis is conducted using the Turkish users. Mentions of Clubhouse have begun on Twitter and Sourtimes platforms in Turkey in early 2021. In this study, the aim is to demonstrate how Clubhouse, a new and different SMP, is evaluated by Twitter and Sourtimes users and to reveal user thoughts about this SMP along the timeline by using sentiment analysis.
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