YouTube video identificators analyzed in the paper "An analytical and experimental study of the energy transition discourse on YouTube"

This repository contains the video identifiers of the YouTube content analysed in the paper "An analytical and experimental study of the energy transition discourse on YouTube". This repository contains two files own_videos.csv and keyword_videos.csv. YouTube original content The file own_videos.csv is a CSV file listing the YouTube videos used in the analysis of 15 challenges conducted for this study. Each challenge generated four video formats (two complete versions and two brief versions), and every video was published on two mirror YouTube channels. This results in a total of 120 analysed videos. The CSV file includes one row per video and provides two fields: the unique YouTube ID id and the channel where the video was published. These identifiers allow users to retrieve public metadata directly from the YouTube API or replicate the data collection procedure described in the study. YouTube concept analysis The file keyword_videos.csv is a CSV file listing YouTube videos associated with public discourse on energy management and the energy transition. Using the YouTube Data API’s Search function, we queried 13 key concepts—energy economy, energy supply and demand, geopolitics of energy, electricity market, renewable energy, energy and mobility, energy saving, energy storage, energy transition, energy efficiency, decolonisation, energy model, and energy resources. For each concept, up to 200 Spanish-language videos were retrieved and filtered by language (based on descriptions and transcriptions) and by the presence of energy-related terminology in the video description. After filtering, the final dataset contains 2,108 videos distributed across the 13 concepts. Each row in the CSV includes two fields: the YouTube id and the keyword to which the video belongs. These identifiers allow users to retrieve full public metadata from the YouTube API or replicate the data-collection workflow described in the study. The data collection process was supported by project 23S06035-001, funded by the 2023 Research and Innovation Grant Program of the Barcelona City Council in collaboration with the “La Caixa” Foundation.