Market Sentiment Analysis on The Tourism and Recreation Industry in The IDX Post-Pandemic Using the CRISP-DM Method on Twitter Data

Ida Bagas Gede Dananjaya (), Upayana Wiguna Eka Saputra, Made Andi Pramana Sukarta, Ida Bagus Sanjaya and Cokorda Istri Sri Vidhari
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Ida Bagas Gede Dananjaya: Politeknik Negeri Bali, Tourism Department
Upayana Wiguna Eka Saputra: Politeknik Negeri Bali, Business Administration Department
Made Andi Pramana Sukarta: Bali State Polytechnic, Accounting Department
Ida Bagus Sanjaya: Politeknik Negeri Bali, Business Administration Department
Cokorda Istri Sri Vidhari: Politeknik Negeri Bali, Tourism Department

A chapter in Proceedings of the International Conference on Sustainable Green Tourism Applied Science - Social Applied Science 2024 (ICoSTAS-SAS 2024), 2024, pp 247-255 from Springer

Abstract: Abstract This study aims to find out the positive or negative sentiment of investors on social media Twitter towards 43 companies in the Tourism and Recreation Industry which consists of four sub-industries, namely Hotels, Resorts and Cruiselines, Travel Agencies, Recreational & Sports Facilities, and Restaurants listed on the IDX (Indonesia Stock Exchange) after the Covid-19 pandemic. The sample used is tweet data posted from June 23, 2023, to January 23, 2024, with the keyword issuer code and company name, so that it can be one of the guidelines for making investment decisions based on herding behavior, sentiment analysis is carried out on the social media platform Twitter by using key words of the issuer code and the company’s name in the tourism and recreation industry on the IDX using the CRISP-DM (Cross Industry Standard Process Data) method Mining) with the Naïve Bayes algorithm. Based on the calculation using the CRISP-DM method, the results were obtained in neutral data at 74.11%, positive data at 44.75%, and negative data at 19.28%, with the number of Positive Sentiment Prediction 153, Neutral 152, and Negative 130 on social media Twitter for 43 companies in the Tourism and Recreation Industry.

Keywords: CRISP-DM; Herding Behavior; Naïve Bayes; Sentiment Analisis (search for similar items in EconPapers)
Date: 2024
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DOI: 10.2991/978-94-6463-622-2_28

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