Sentiment Analysis of Twitter Use on Policy Institution Services using Naïve Bayes Classifier Method

Abstract

Twitter is one of the social media used to respond to various services of public service institutions, including the police. The research aim to determine the community's assessment of the service and performance of police institutions delivered via Twitter. This study uses the Naïve Bayes Classifier algorithm to classify topics and public sentiment towards tweets from police agencies. The results obtained were 181 positive tweets, 322 negative tweets, and 33 neutral tweets. Sentiment analysis showed 55% respondent positively to police activities, 19.1% responded positively to public comments, and 91.8% respondent positively to social services. It can be concluded that most people support police activities and services, but most people are still dissatisfied with police performance.

Arabic Sentiment Analysis for Twitter Data: A Systematic Literature Review

“…SA is a set of processes that are applied widely in computer science studies to analyze and examine semantics, words, and tweet syntax to determine the emotions in the text [6]. The main purpose of SA using Twitter data is to classify tweets into three polarities (positive, negative, or natural) based on the statements or words contained in that tweet [7]. In this section, the main finding of this systematic review regarding ASA using the Twitter platform are presented and discussed.…”