Technology

4 datasets tagged as the tag “Technology”.

4 datasets.

MADOC: Reddit / technology Analyzed

A MADOC (Reddit, technology) dataset of 611,131 users and 2,052,369 reply edges from 11,766,082 interactions, collected by Dankulov et al. via platform APIs, published at ICWSM 2025. Each record contains user-user reply edges, post and comment text, per-record sentiment scores (VADER and TextBlob), subjectivity scores, and toxicity scores (ToxiGen). The dataset is notable for its FAIR-compliant dataset with pre-computed NLP quality labels (sentiment, subjectivity, toxicity) per record, enabling network analysis and content quality research without additional annotation. Intended for research into social network analysis, toxicity detection, cross-platform community dynamics, misinformation research, and hate speech propagation studies.

11.8M records611.1K nodes2.1M edges2025

Voat — v/technology Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 29,282 submissions, 171,228 comments, 33,116 users, 103,763 collaboration edges, collected by Mekacher & Papasavva (ICWSM 2022) via full platform crawl. Each record contains user nodes (registration date, moderation status), directed weighted edges (commenter→submitter, weight=upvotes+1), submission titles and bodies, comment text, upvotes, downvotes, depth. Complete dataset for the Voat subverse v/technology, covering its full lifetime on the platform (2013–2020). Includes all 29,282 submissions and 171,228 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

191.1K records33.1K nodes103.8K edges2022

MADOC: Voat / technology Analyzed

A MADOC (Voat, technology) dataset of 14,397 users and 41,519 reply edges from 83,185 interactions, collected by Dankulov et al. via platform APIs, published at ICWSM 2025. Each record contains user-user reply edges, post and comment text, per-record sentiment scores (VADER and TextBlob), subjectivity scores, and toxicity scores (ToxiGen). The dataset is notable for its FAIR-compliant dataset with pre-computed NLP quality labels (sentiment, subjectivity, toxicity) per record, enabling network analysis and content quality research without additional annotation. Intended for research into social network analysis, toxicity detection, cross-platform community dynamics, misinformation research, and hate speech propagation studies.

83.2K records14.4K nodes41.5K edges2025

Blog Authorship Corpus — Technology Bloggers Analyzed

A Blogger.com (2004) dataset of 570 bloggers, 906 posts, collected by Schler et al. for AAAI 2006. Each record contains blog post text, gender, age, industry, astrological sign. Historical blog corpus from 2004 with rich metadata per blogger (gender, age, industry, astrological sign). Balanced across age groups and genders.. Suitable for authorship attribution, stylistic analysis, demographic language variation, historical NLP.

570 records2006