Sentiment Analysis of the Indonesian National Team in the 2026 World Cup Qualification on Social Media X Using Naive Bayes

2026-10-10T07:23:54+00:00

The increasing public attention toward the Indonesian national football team during the 2026 FIFA World Cup qualification has generated diverse opinions on social media X. This study analyzes public sentiment expressed in X posts concerning the Indonesian national team's performance during the qualification period using a Naive Bayes classifier. A total of 1,600 tweets were initially collected using the Tweet Harvest tool with the keyword “Indonesia World Cup 2026 qualification.” After data cleaning, duplicate and missing-value removal, and sentiment labeling using an Indonesian sentiment lexicon, 750 final labeled tweets were used for classification into positive and negative sentiment classes. The data were processed through tokenization, case folding, Indonesian stopword removal, token filtering, and TF-IDF weighting. The Naive Bayes model was evaluated using a 90:10 training-test split and a confusion matrix. On the test set of 75 tweets, the model achieved an accuracy of 68.00%, with a precision of 50.00% and recall of 62.50% for the positive class. The results indicate moderate classification performance rather than consistently high predictive performance. The contribution of this study is to provide an event-specific empirical analysis of sentiment toward the Indonesian national team during the 2026 World Cup qualification and to establish a baseline for sentiment classification using Naive Bayes on Indonesian-language X data. The findings may provide contextual information about sentiments expressed by the analyzed X users, although they should not be interpreted as representing the sentiment of the Indonesian population as a whole.

Journal Of Data Science

Sentiment Analysis of the Indonesian National Team in the 2026 World Cup Qualification on Social Media X Using Naive Bayes