Brazilian Elections YouTube Comments Dataset (2018-2022)

This dataset provides a comprehensive analysis of YouTube comments related to Brazilian election candidates for the years 2018 and 2022. The dataset is organized into two folders: video_gender_mapping_BR_elections: This folder contains individual files, each corresponding to a YouTube channel analyzed. Each file includes the following fields: channelId: YouTube channel identifier channelTitle: YouTube channel title videoId: YouTube video identifier publishedAt: Datetime of when the video was published year_month: Year and month of when the video was published views: Number of views of the video comments: Number of total comments on the video likes: Number of total likes on the video match_type: Type of match considering candidate name and video title/description (T for Title, D for Description, TD for both) match_result: Array of JSON containing positive matches based on race, elective office, title/description match, and gender match_cargos: List of elective offices that appear in the match match_genero: Overview of gender types (M for male, F for female, MF for both) match_raca: Overview of races for all matched elective offices (BR for white, AM for yellow, PA for brown, PR for black, IN for Indian, NA for None of the above) match_genero_raca: Array of gender and race concatenated for each matched candidate comments_folders: This file provides a sample of comments collected from the videos analyzed in the first file. It includes the following fields: id: Comment identifier videoId: Video identifier where the comment is published textDisplay: Comment as displayed on the YouTube platform textDisplay_len: Number of characters in the displayed comment textOriginal: Encoded comment text textOriginal_len: Number of characters in the original comment text authorDisplayName: Name of the comment author authorChannelId: Comment author channel identifier publishedAt: Timestamp of when the comment was published likes: Number of likes on the comment This dataset offers valuable insights into YouTube interactions surrounding Brazilian elections, including demographic and sentiment analysis based on candidate information, gender, and race. Researchers can utilize this dataset for a detailed examination of public engagement and sentiment on political content during the specified election periods.