Analysis of Public Sentiment about Sea Games eSport on Twitter using the Adaboost Algorithm

Muhammad Syifa; Nurul Khairina; Dian  Noviandri; Yuan  Anisa; Nanda  Novita

doi:10.33365/teknoinfo.v20i2.1706

Muhammad Syifa Universitas Medan Area
Nurul Khairina Universitas Medan Area
Dian Noviandri Universitas Medan Area
Yuan Anisa Universitas Medan Area
Nanda Novita Universitas Medan Area

DOI: https://doi.org/10.33365/teknoinfo.v20i2.1706

Keywords: Sentiment, eSports, Adaboost, Classification

Abstract

This research aims to analyze public sentiment towards the Sea Games eSports as reflected in conversations on the Twitter platform. The two main issues in focus are how the public sentiment towards the Sea Games eSports event and whether their responses tend to be positive or negative towards the event. The research method used is the Adaboost Algorithm, a technique in data mining that aims to improve classification accuracy. Adaboost was used to analyze sentiment from Twitter conversation data by using feature selection to select weak classification functions, then combining them into a new classification function. The results showed that the highest evaluation was achieved in the 2nd test with the use of training data by 90% and testing by 10%, which resulted in an accuracy of 98%. Sentiment analysis of the Sea Games eSports showed that the majority of Twitter users expressed 111 (95.7%) positive sentiments, while only 5 (4.3%) negative sentiments. This indicates that people tend to give positive responses to the Sea Games eSports event. This research illustrates that sentiment analysis using the Adaboost Algorithm is able to provide accurate results in mapping public responses to the Sea Games eSports event on Twitter. The implication is that the strong support from the community towards this event can be an important basis for further development and promotion of Sea Games eSports.

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