Geosocial Media's Perspective on Energy: A Text Classification Approach using Natural Language Processing

This repository contains the restricted access Tweet datasets used in the study "Geosocial Media’s Perspective on Energy: A Text Classification Approach using Natural Language Processing". The aim of the study was to examine public opinion on fossil fuels, nuclear energy, and renewable sources (solar and wind) using Twitter data and natural language processing techniques. The following materials are included: Raw Tweet datasets ("Twitter_API_datasets.zip"): Three separate CSV files containing English-language tweets related to fossil energy, nuclear energy, and solar & wind energy, collected using the Twitter Academic Research API v2. Each dataset spans a different time range depending on data availability. Note:These restricted-access Tweet datasets are required to fully execute the analysis provided in the public Zenodo repository, which contains the code, labeled datasets, interactive maps, and supplementary materials used in the study. Users may request access to these raw Twitter datasets here to replicate and validate the study’s findings.本仓库收录了研究《Geosocial Media’s Perspective on Energy: A Text Classification Approach using Natural Language Processing》中所使用的受限访问推文数据集。本研究旨在借助推特（Twitter）数据与自然语言处理（Natural Language Processing）技术，探析公众对于化石燃料、核能及可再生能源（太阳能与风能）的舆论态度。本仓库包含以下素材： 原始推文数据集（"Twitter_API_datasets.zip"）：包含三份独立的逗号分隔值（CSV）文件，均通过推特学术研究API v2（Twitter Academic Research API v2）采集，涵盖与化石能源、核能、太阳能与风能相关的英文推文。各数据集的时间跨度根据对应数据的实际可获取情况确定。 注意：此类受限访问推文数据集是完整复现公开Zenodo仓库中所提供的分析流程的必要资源，该公开仓库收录了本研究使用的代码、标注数据集、交互式地图及补充材料。用户可通过此处申请获取这些原始推特数据集，以复现并验证本研究的结论。