Indonesian Twitter Dataset for Hostile and Benevolent Misogyny Classification (ID-Misogyny) Dataset

Published: 14 September 2026| Version 2 | DOI: 10.17632/8fyyys33rh.2
Contributors:
,
,
,
,

Description

ID-Misogyny Tweets Dataset is a collection of Indonesian Twitter/X data annotated with hostile and benevolent misogyny labels. The data were collected from Twitter/X using 18 predefined Indonesian-language search keywords, split across benevolent-sexism and hostile-sexism categories, spanning January 2023 to July 2026. The dataset contains 5,563 tweets classified into three categories, i.e., Hostile Misogyny, Benevolent Misogyny, or Non-Misogyny. A group of three annotators does the annotation process to provide misogyny labels by following annotation criteria grounded in Glick and Fiske's Ambivalent Sexism Inventory, reviewed by an expert in clinical psychology. Other attributes related to the tweet are also extracted, such as Retweet Count, Reply Count, Like Count, Quote Count, View Count, and Bookmark Count, to support further research.

Files

Institutions

Categories

Social Media, Natural Language Processing, Text Processing, Text Mining, Gender-Based Violence

Licence