A Manufacturing company internal email system (Poland) dataset of 167 nodes and 5,784 edges, collected by Michalski et al. via corporate email logs. Each record contains directed: True, weighted: True, signed: False, temporal: True. Temporal directed email communication network of 167 employees at a manufacturing company over 10 months, with Unix timestamps per message. Useful for studying organizational communication patterns.. Suitable for organizational network analysis, temporal email networks, community detection. The file holds 82,927 e-mails, one row per message; the edge count of 5,784 counts distinct pairs.
A ACM Hypertext 2009 conference (Turin, Italy) dataset of 113 nodes and 2,196 edges, collected by SocioPatterns collaboration via RFID proximity sensing. Each record contains directed: False, weighted: True, signed: False, temporal: True. Face-to-face contact network of 113 conference attendees over 2.5 days, captured at 20-second resolution via RFID badges. Canonical dataset for studying conference social dynamics.. Suitable for temporal contact network analysis, community detection, epidemic modeling. The file holds 20,818 contacts, one row per 20-second face-to-face contact; the edge count of 2,196 counts distinct pairs.
A MIT Media Lab (mobile phone Bluetooth proximity sensing) dataset of 96 nodes and 2,539 edges, collected by Nathan Eagle & Alex Pentland via mobile phone study. Each record contains directed: False, weighted: True, signed: False, temporal: True. Bluetooth proximity contact network of 100 MIT students and faculty over 9 months. One of the earliest large-scale mobile sensing datasets, with temporal edges capturing when people were physically near each other.. Suitable for temporal network analysis, proximity sensing, community detection, mobility.
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.
A Twitter, Facebook, and Instagram dataset of 44 quarterly records spanning Q1 2010 to Q4 2020, collected by Margaretha Martinez via CNBC and Statista (2021). Each record contains quarter label, Twitter MAU (millions), Facebook MAU (millions), Instagram MAU (millions). A longitudinal quarterly time-series tracking monthly active user counts for three major social media platforms across a decade of growth. Suitable for platform growth analysis, social media market trends, digital media landscape studies, longitudinal comparison research.
Google
Wikipedia
Facebook
Instagram
Twitter (X)