A Twitter (aggregate) dataset of 4,709,404 topic-related tweets across 6 social issues, collected by NORC at the University of Chicago. Each record contains date, topic, daily volume, VADER compound sentiment, pos/neg ratio, account type (community/bot/news/government/activist), US state. Aggregate Twitter data on six politically salient social issues with daily volume and VADER sentiment scores 2016-2022, including unique bot-vs-community account type breakdowns and US state-level marijuana discourse data. Suitable for political communication, sentiment trends, bot detection, state-level public opinion, longitudinal social issue analysis.
A Multiple (Wikipedia, GDELT, Google Trends) dataset of 51 weeks of cross-platform attention data across 6 regions, collected by Luke Steuber via Wikipedia API, GDELT Project, and Google Trends (2020-2025). Each record contains weekly attention scores by region, component metrics (Google Trends, GDELT, Wikipedia), and regional composite scores. A unified, weekly time-series of public attention to the United States from three independent sources, broken down by global region, enabling multi-perspective analysis of attention dynamics. Suitable for information cascade, event detection, public health monitoring, political communication, media analysis, attention tracking, regional sentiment analysis.