Datasets from Google services that have no platform of their own here, such as the Google+ social network (2011–2019), Google Scholar citation profiles and search-interest data. Website ↗
A Google+ dataset of 211,187 users, 1,506,896 circle memberships, collected by Fire et al. via Google+ API (2013). Each record contains directed edges between Google+ users representing circle memberships (user → circle). Google+ social graph capturing directed circle relationships, where users add others to their circles, creating a directed social graph structure. Suitable for link prediction, social network analysis, community detection, circle-based social behavior analysis.
A Google+ (now defunct) dataset of 102,100 nodes and 13,548,655 directed edges across 132 ego networks with ground-truth circles, collected by McAuley and Leskovec (Stanford, 2012) from public Google+ profiles. Each record contains directed follow edges, ground-truth circle memberships (Google+ circles shared publicly), anonymized node feature vectors representing profile attributes. 133 Google+ ego networks with publicly shared ground-truth circles from users who voluntarily released their circle data, providing a uniquely clean community ground-truth from a directed social platform. Suitable for overlapping community detection, ego network analysis, directed social circle inference, link prediction.
A Google Scholar dataset of 82,937 papers, 148,116 citations, collected by Google Scholar via academic citation data. Each record contains citation edges between papers, node IDs, node names (titles), node types (paper, author, etc.), edge types (cites, etc.). Academic citation network from Google Scholar, capturing the flow of scientific knowledge through citation relationships. Suitable for citation analysis, academic network analysis, research impact, knowledge flow studies, scholarly communication.
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.
Academia.edu
Wikipedia