Analysis of Sexual Harassment Tweet Sentiment on Twitter in Indonesia using Naïve Bayes Method through National Institute of Standard and Technology Digital Forensic Acquisition Approach
Kholiq, Budiman (2020) Analysis of Sexual Harassment Tweet Sentiment on Twitter in Indonesia using Naïve Bayes Method through National Institute of Standard and Technology Digital Forensic Acquisition Approach. Analysis of Sexual Harassment Tweet Sentiment on Twitter in Indonesia using Naïve Bayes Method through National Institute of Standard and Technology Digital Forensic Acquisition Approach, 2 (2). p. 21. ISSN 2714-9714
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Abstract
In this era, the internet is commonly used in society, especially for social media. Social media is an open and unlimited medium of communication where people can freely express their opinions. However, nowadays, many people are abusing social media to do negative things; online sexual harassment is an example. This research was conducted based on previous research or literature studies; the research results showed various sentiment analysis results using the Naïve Bayes classifier method through the digital forensic acquisition approach. The study aims to identify sexual harassment by using sentiment analysis from Twitter and measuring grouping results' accuracy with the Naïve Bayes method. In this study, sexual harassment was identified using analytical sentiment by testing 300 tweets data consisting of 30 queries from Twitter. The result of sentiment analysis from 300 Twitter scraping data shows that the value of negative sentiment is higher than positive sentiment with an average total of 69.7%. From this sentiment, Twitter becomes one of the free communication media and vulnerable to verbal sexual harassment through tweets in Indonesia.
Item Type: | Article |
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Subjects: | T Technology > Information and Computer > Website T Technology > Information and Computer > Expert System T Technology > Information and Computer > Information System |
Fakultas: | Fakultas Matematika dan Ilmu Pengetahuan Alam > Ilmu Komputer, S1 |
Depositing User: | dina nurcahyani perpus |
Date Deposited: | 12 Mar 2021 03:38 |
Last Modified: | 12 Mar 2021 03:38 |
URI: | http://lib.unnes.ac.id/id/eprint/43356 |
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