News

48 datasets tagged as the topic “News”.

48 datasets.

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NELA-PS: Pink Slime News Dataset Analyzed

A NELA-PS (pink slime local news) dataset of 7,910,965 articles from 1,093 pink slime news sources, collected by Horne and Gruppi, published via Harvard Dataverse (2024). Each record contains full article text, headline, source outlet name, publication date, author, location, network, and URL. The dataset is notable for its largest available dataset of pink slime news — low-quality partisan content systematically framed as authentic local news, spanning 1,093 outlets over 2.5 years with stratified cross-outlet topic modeling. Intended for research into misinformation detection, local news ecosystem analysis, partisan content identification, and pink slime outlet characterisation.

7.9M records2024

Slashdot Online Conversation Threads (Aug 2005–Aug 2006) Analyzed

A Slashdot dataset of 10,019 discussion threads, August 2005 to August 2006, from the Online Conversation Threads repository of Aragón et al. (ICWSM 2017): 2,084,864 nodes (articles and comments) and 2,075,611 comment-to-parent reply edges, with comment text, moderation scores, timestamps and thread depth. Suitable for online discourse analysis, conversation dynamics and hierarchical reply-tree structure.

2.1M records2.1M nodes2.1M edges2008

Voat — v/news Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 176,948 submissions, 1,081,119 comments, 36,459 users, 469,843 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/news, covering its full lifetime on the platform (2013–2020). Includes all 176,948 submissions and 1,081,119 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

1.2M records36.5K nodes469.8K edges2022

Digg Friendship Network (December 2010) Analyzed

A Digg (social news) dataset of 771,231 users and 5,911,205 friendship edges, collected by Mithila Nagendra via Digg crawl (December 2010). Each record contains user-user friendship edges and user IDs. The dataset is notable for its friendship network from the pre-v4 Digg social news platform, where users voted stories up (digging) or down (burying). Intended for research into social network analysis, community detection, information diffusion, and social news platform structure studies.

771.2K records771.2K nodes5.9M edges2010

News Sharing Networks — Information Polluters (Nature Human Behaviour 2022) Analyzed

A Twitter dataset of 404,615 nodes, 434,963 edges, collected by Pierri et al. (OSoMe/Indiana University + Politecnico di Milano), 2020. Each record contains retweet network (uid1, uid2), user-domain bipartite network, user co-sharing network. Twitter news-sharing network revealing information polluters through retweet and co-sharing patterns.. Suitable for Information polluter identification, news sharing network analysis, source credibility..

404.6K records404.6K nodes435K edges2024

Anatomy of an Online Misinformation Network (PLOS ONE 2018) Analyzed

A Twitter dataset of 346,573 nodes, 1,091,552 edges, collected by Shao et al. via Hoaxy API (OSoMe/Indiana University). Each record contains from_user_id, to_user_id, tweet_id, tweet_created_at, site_type (claim/fact-checking). Retweet diffusion network of misinformation and fact-checking content surrounding the 2016 US election; distinguishes claim vs. fact-checking retweets.. Suitable for Misinformation diffusion, fact-checking network analysis, network epidemiology..

346.6K records346.6K nodes1.1M edges2018

MemeTracker: News Cycle Phrase Cluster Network Analyzed

A Web (news sites and blogs, Aug 2008–Apr 2009) dataset of 71,568 phrase clusters, 310,457 unique phrase nodes, 238,889 directed root→variant edges, 71,568 phrases in text corpus, collected by Leskovec et al. via web crawl of 1.5M articles/day, August 2008 to April 2009, distributed by SNAP. Each record contains phrase cluster graph where nodes are natural language phrases extracted from news articles and blogs; directed edges from root phrase to variant phrases within each cluster; edge weight = variant phrase frequency; covers the 2008 US election, financial crisis, and other major news events. The dataset is notable for its foundational information diffusion dataset capturing how phrases mutate and propagate across mainstream media and blogs; the cluster graph encodes phrase similarity and co-occurrence structure, enabling study of linguistic variation in news cycles. Intended for research into information diffusion modeling, meme propagation analysis, phrase clustering, linguistic variation in news media, temporal network analysis, and graph-based NLP research.

310.5K records310.5K nodes238.9K edges2009

ReCOVery: COVID-19 News Credibility Repository Analyzed

A ReCOVery (news credibility repository) dataset of 2,029 news articles with reliability labels and social media engagement, collected by Zhou, Mulay, Ferrara, and Zafarani via news websites and Twitter (2020). Each record contains news article title and body, reliability label (1=reliable, 0=unreliable), publisher, political bias, country, author, and social media engagement data. The dataset is notable for its multimodal repository combining news content with social media engagement, designed for COVID-19 news credibility research. Intended for research into fake news detection, credibility assessment, political bias analysis, and multimodal misinformation research.

142.8K records142.8K nodes140.8K edges2020
graphimagetextTwitter (X)CovidCrisisHealth+2

Misinformation & Fake News Text Dataset Analyzed

A News Articles (multiple sources) dataset of 85,917 articles (43,610 fake, 34,941 true, 7,366 russian propaganda), collected by Steven Peutz via Kaggle (2022); Russian propaganda subset sourced from the EUvsDisinfo Project (2015-present). Each record contains full article text and veracity label (fake, true, or russian_propaganda). combination of general fake/true news articles with a dedicated Russian propaganda subset from the EUvsDisinfo database, enabling comparative analysis across disinformation types. Suitable for fake news detection, misinformation topic modeling, propaganda characterization, and classification benchmarking.

85.9K records2022

Voat — v/Worldnews Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 20,237 submissions, 63,811 comments, 7,956 users, 33,170 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/Worldnews, covering its full lifetime on the platform (2013–2020). Includes all 20,237 submissions and 63,811 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

78.8K records8K nodes33.2K edges2022

Social Bookmarking Dataset — GiveALink November 2009 Analyzed

A Delicious dataset of 61,665 bookmarks, collected by OSoMe / GiveALink project, November 2009. Each record contains bookmark URL, timestamp, user tags. Daily Delicious social bookmarking snapshots from November 2009; each bookmark includes URL, Unix timestamp, and free-form user tags.. Suitable for Social bookmarking analysis, tag-based topic modeling, information diffusion, temporal content analysis..

61.7K records2006

Slashdot Discussion Thread Network Analyzed

A Slashdot (technology news discussion forum) dataset of 51,083 nodes and 131,175 edges, collected by KONECT via Slashdot crawl. Each record contains directed: True, weighted: True, temporal: True. Directed reply network of Slashdot discussion threads — different from the Slashdot Zoo signed network, this captures comment reply structure.. Suitable for discussion thread analysis, online community structure, reply network analysis.

51.1K records51.1K nodes131.2K edges2008

ISOT Fake News Dataset Analyzed

A ISOT (fake news dataset) dataset of 44,898 news articles labeled fake/real, collected by ISOT via Reuters and various sources (2017). Each record contains news article text (title + content) and binary label (is_fake: 1=fake, 0=real). The dataset is notable for its well-balanced dataset of fake and real news articles for misinformation research. Intended for research into fake news detection, text classification, and misinformation analysis.

44.9K records2017

iDRAMA-Scored: c/News Analyzed

A Scored.co (c/News) dataset of 18,801 submissions and 18,518 comments from 647 unique authors in c/News (2020-2023), collected by iDRAMA Lab via Scored.co API (2024). Each record contains post/comment text, author, score up/down, NSFW/deleted/twitter-crosspost flags, date, UUID. c/News on Scored.co — General news discussion. 37,319 total posts from 647 authors over 4 years. Suitable for deplatforming research, community behavior analysis, alternative platform discourse, content moderation effects, longitudinal community evolution.

37.3K records648 nodes647 edges2024

Facebook Pages — Media Category (Nov 2017) Analyzed

A Facebook dataset of 27,917 pages, 206,259 mutual likes, collected by Rozemberczki et al. via the Facebook Graph API (November 2017). Each record contains undirected edges between blue verified Facebook media pages that mutually liked each other, with node attributes including page name and raw Facebook ID. Graph of blue verified Facebook media pages, where edges represent mutual likes between pages, capturing how users discover and engage with media and news content. Suitable for community detection in social networks, graph embedding, media influence analysis, news consumption studies, journalism and media network analysis.

27.9K records27.9K nodes206.3K edges2019

Voat — v/politicalnews Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 17,135 submissions, 9,733 comments, 1,957 users, 3,783 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/politicalnews, covering its full lifetime on the platform (2013–2020). Includes all 17,135 submissions and 9,733 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

26.1K records2K nodes3.8K edges2022

Voat — v/WorldToday Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 12,898 submissions, 13,124 comments, 1,885 users, 2,139 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/WorldToday, covering its full lifetime on the platform (2013–2020). Includes all 12,898 submissions and 13,124 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

24.8K records1.9K nodes2.1K edges2022

FakeNewsNet: Fake News Detection with Social Context Analyzed

A FakeNewsNet (fake news with social context) dataset of 23,196 news articles labeled fake/real with social media context, collected by Shu et al. via Politifact and GossipCop (2019). Each record contains news title, article text, binary label (0=real, 1=fake), source (politifact/gossipcop), publish date, and URL. The dataset is notable for its dataset with social context and spatiotemporal information for studying fake news propagation. Intended for research into fake news detection, social media analysis, misinformation propagation, and multimodal research.

23.2K records2019

Voat — v/Drudge Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 8,394 submissions, 9,913 comments, 897 users, 896 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/Drudge, covering its full lifetime on the platform (2013–2020). Includes all 8,394 submissions and 9,913 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

18K records897 nodes896 edges2022

Meneame Media Bias Dataset Analyzed

A Meneame dataset of 14,995 articles, 20,000 comments, 45,392 users, collected by Meneame Media Bias Team. Each record contains article title, text, bias labels, sentiment, emotion scores, karma features, user-outlet graph. Spanish social news aggregator dataset with media bias labels and rich interaction features. Suitable for media bias detection, sentiment analysis, social news dynamics, graph analysis.

15K records49.6K nodes519.5K edges2026

Voat — v/USNews Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 5,890 submissions, 8,027 comments, 1,884 users, 3,883 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/USNews, covering its full lifetime on the platform (2013–2020). Includes all 5,890 submissions and 8,027 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

13.3K records1.9K nodes3.9K edges2022

LIAR: Fake News Detection Benchmark Analyzed

A LIAR (fact-checking benchmark) dataset of 12,789 labeled claim statements from Politifact, collected by Wang via Politifact fact-checking (2017). Each record contains claim text, 6-class veracity label, speaker metadata (party, state, job title), credit history counts (barely_true/false/half_true/mostly_true/pants_fire), and context. The dataset is notable for its benchmark dataset for fake news detection with fine-grained 6-class labels, rich speaker metadata, and credit history. Intended for research into fake news detection, fact-checking, political discourse analysis, and misinformation research.

12.8K records2017

Twitter Financial News Sentiment Dataset Analyzed

A Twitter dataset of 11,929 labeled financial tweets, collected by zeroshot via Twitter API. Each record contains tweet text, sentiment label (positive/negative/neutral), sentiment value (0/1/2), train/valid split. A labeled dataset of tweets about financial news, with sentiment annotations for stock market-related content. Suitable for sentiment analysis, financial NLP, stock market prediction, social media analytics, natural language processing.

11.9K records2023

TUAW Blog Post Dataset Analyzed

A TUAW (The Unofficial Apple Weblog) dataset of 10,485 blog posts, collected by Agarwal, Tang, Liu, and Yu via TUAW crawl (2004-2007). Each record contains blog post title, text, author, categories, publication date, inlinks, outlinks, and comment counts. The dataset is notable for its blog dataset with rich metadata, representing a closed community of Apple-focused bloggers. Intended for research into influential blogger identification, blog post analysis, text classification, and influence modeling.

10.5K records10.5K nodes2008

Fake News Detection Dataset Analyzed

A News Articles (multiple sources) dataset of 9,900 news articles (5,000 fake, 4,900 real), collected by Vishakh Dapat via Kaggle (2023). Each record contains full article text and binary veracity label (Fake or Real). The dataset is notable for its balanced binary-labeled news corpus with approximately equal proportions of fake and real articles, making it well-suited as a classification benchmark. Intended for research into fake news detection, text classification benchmarking, misinformation topic modeling, and NLP feature engineering.

9.9K records2023

Usenet Sample — news.* hierarchy Analyzed

A Usenet (sample) dataset of 7,361 posts from 53 newsgroups, collected by OwnedByDanes via Hugging Face. Each record contains post text, newsgroup, date, author, subject. Sample of Usenet posts from 1980–2013, with 5,000 posts per top‑level hierarchy. Covers comp.*, sci.*, rec.*, alt.*, etc.. Suitable for historical discourse analysis, early internet culture, topic evolution, authorship attribution.

7.4K records2026

Fortune 100 BLM Response Dataset Analyzed

A Twitter dataset of 6,184 tweets from Fortune 100 companies, collected by Kevin McElwee via Twitter API. Each record contains tweet text, corporation name, sector, timestamp, hashtags, racial justice label, BLM mention, Juneteenth mention, donation mention. A manually annotated dataset of tweets from Fortune 100 companies during the 2020 Black Lives Matter protests, capturing corporate responses to a major social movement. Suitable for corporate activism, social movement response, political communication, crisis communication, public relations, brand activism.

6.2K records2020

Voat — v/newsandpolitics Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 3,465 submissions, 117 comments, 73 users, 66 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/newsandpolitics, covering its full lifetime on the platform (2013–2020). Includes all 3,465 submissions and 117 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

3.6K records73 nodes66 edges2022

CLEF CheckThat! 2025 Subjectivity — Arabic Analyzed

A CLEF CheckThat! 2025 subjectivity task (arabic) dataset of 2,446 sentences with subjectivity labels (43.1% subjective), collected by CLEF CheckThat! Lab organizers (2025). Each record contains sentence text, binary subjectivity label (SUBJ/OBJ), sentence ID, conflict resolution flag. CLEF 2025 CheckThat! subjectivity (arabic) provides 2,446 news sentences annotated for subjectivity — whether the sentence expresses opinions (SUBJ) or facts (OBJ). Suitable for subjectivity detection, opinion mining, NLP classification, news objectivity analysis, multilingual text classification.

2.4K records2025

CHECKED: Chinese COVID-19 Fake News Dataset Analyzed

A Weibo (CHECKED dataset) dataset of 2,104 microblogs with engagement and expert analysis, collected by Yang, Zhou, and Zafarani via Weibo (2020-2021). Each record contains microblog text, images, videos, engagement metrics (comments, reposts, likes), and expert analysis for fake news. The dataset is notable for its first Chinese COVID-19 fake news dataset with expert analysis, anonymized user IDs, and rich social interaction data. Intended for research into fake news detection, misinformation analysis, Chinese NLP, social network analysis, and public health communication.

2.1K records2021

CLEF CheckThat! 2024 Subjectivity — Italian Analyzed

A CLEF CheckThat! 2024 subjectivity task (italian) dataset of 1,613 sentences with subjectivity labels (23.7% subjective), collected by CLEF CheckThat! Lab organizers (2024). Each record contains sentence text, binary subjectivity label (SUBJ/OBJ), sentence ID, conflict resolution flag. CLEF 2024 CheckThat! subjectivity (italian) provides 1,613 news sentences annotated for subjectivity — whether the sentence expresses opinions (SUBJ) or facts (OBJ). Suitable for subjectivity detection, opinion mining, NLP classification, news objectivity analysis, multilingual text classification.

1.6K records2024

CLEF CheckThat! 2025 Subjectivity — Italian Analyzed

A CLEF CheckThat! 2025 subjectivity task (italian) dataset of 1,613 sentences with subjectivity labels (23.7% subjective), collected by CLEF CheckThat! Lab organizers (2025). Each record contains sentence text, binary subjectivity label (SUBJ/OBJ), sentence ID, conflict resolution flag. CLEF 2025 CheckThat! subjectivity (italian) provides 1,613 news sentences annotated for subjectivity — whether the sentence expresses opinions (SUBJ) or facts (OBJ). Suitable for subjectivity detection, opinion mining, NLP classification, news objectivity analysis, multilingual text classification.

1.6K records2025

CLEF CheckThat! 2023 Subjectivity — Italian Analyzed

A CLEF CheckThat! 2023 subjectivity task (italian) dataset of 1,613 sentences with subjectivity labels (23.7% subjective), collected by CLEF CheckThat! Lab organizers (2023). Each record contains sentence text, binary subjectivity label (SUBJ/OBJ), sentence ID, conflict resolution flag. CLEF 2023 CheckThat! subjectivity (italian) provides 1,613 news sentences annotated for subjectivity — whether the sentence expresses opinions (SUBJ) or facts (OBJ). Suitable for subjectivity detection, opinion mining, NLP classification, news objectivity analysis, multilingual text classification.

1.6K records2023

CLEF CheckThat! 2024 Subjectivity — Arabic Analyzed

A CLEF CheckThat! 2024 subjectivity task (arabic) dataset of 1,185 sentences with subjectivity labels (23.6% subjective), collected by CLEF CheckThat! Lab organizers (2024). Each record contains sentence text, binary subjectivity label (SUBJ/OBJ), sentence ID, conflict resolution flag. CLEF 2024 CheckThat! subjectivity (arabic) provides 1,185 news sentences annotated for subjectivity — whether the sentence expresses opinions (SUBJ) or facts (OBJ). Suitable for subjectivity detection, opinion mining, NLP classification, news objectivity analysis, multilingual text classification.

1.2K records2024

CLEF CheckThat! 2023 Subjectivity — Arabic Analyzed

A CLEF CheckThat! 2023 subjectivity task (arabic) dataset of 1,185 sentences with subjectivity labels (23.6% subjective), collected by CLEF CheckThat! Lab organizers (2023). Each record contains sentence text, binary subjectivity label (SUBJ/OBJ), sentence ID, conflict resolution flag. CLEF 2023 CheckThat! subjectivity (arabic) provides 1,185 news sentences annotated for subjectivity — whether the sentence expresses opinions (SUBJ) or facts (OBJ). Suitable for subjectivity detection, opinion mining, NLP classification, news objectivity analysis, multilingual text classification.

1.2K records2023

DNC Email Co-Recipient Network Analyzed

A Democratic National Committee (email communications, 2016) dataset of 906 nodes and 10,429 edges, collected by WikiLeaks DNC email leak. Each record contains directed: False, weighted: True, signed: False, temporal: False. Weighted undirected co-recipient network from the leaked DNC emails — two people are connected if they appeared together on email threads, with edge weights indicating co-occurrence frequency.. Suitable for political network analysis, email network analysis, community detection.

906 records906 nodes10.4K edges2013

CLEF CheckThat! 2023 Subjectivity — English Analyzed

A CLEF CheckThat! 2023 subjectivity task (english) dataset of 830 sentences with subjectivity labels (35.9% subjective), collected by CLEF CheckThat! Lab organizers (2023). Each record contains sentence text, binary subjectivity label (SUBJ/OBJ), sentence ID, conflict resolution flag. CLEF 2023 CheckThat! subjectivity (english) provides 830 news sentences annotated for subjectivity — whether the sentence expresses opinions (SUBJ) or facts (OBJ). Suitable for subjectivity detection, opinion mining, NLP classification, news objectivity analysis, multilingual text classification.

830 records2023

CLEF CheckThat! 2024 Subjectivity — English Analyzed

A CLEF CheckThat! 2024 subjectivity task (english) dataset of 830 sentences with subjectivity labels (35.9% subjective), collected by CLEF CheckThat! Lab organizers (2024). Each record contains sentence text, binary subjectivity label (SUBJ/OBJ), sentence ID, conflict resolution flag. CLEF 2024 CheckThat! subjectivity (english) provides 830 news sentences annotated for subjectivity — whether the sentence expresses opinions (SUBJ) or facts (OBJ). Suitable for subjectivity detection, opinion mining, NLP classification, news objectivity analysis, multilingual text classification.

830 records2024

CLEF CheckThat! 2025 Subjectivity — English Analyzed

A CLEF CheckThat! 2025 subjectivity task (english) dataset of 830 sentences with subjectivity labels (35.9% subjective), collected by CLEF CheckThat! Lab organizers (2025). Each record contains sentence text, binary subjectivity label (SUBJ/OBJ), sentence ID, conflict resolution flag. CLEF 2025 CheckThat! subjectivity (english) provides 830 news sentences annotated for subjectivity — whether the sentence expresses opinions (SUBJ) or facts (OBJ). Suitable for subjectivity detection, opinion mining, NLP classification, news objectivity analysis, multilingual text classification.

830 records2025

CLEF CheckThat! 2025 Subjectivity — German Analyzed

A CLEF CheckThat! 2025 subjectivity task (german) dataset of 800 sentences with subjectivity labels (38.5% subjective), collected by CLEF CheckThat! Lab organizers (2025). Each record contains sentence text, binary subjectivity label (SUBJ/OBJ), sentence ID, conflict resolution flag. CLEF 2025 CheckThat! subjectivity (german) provides 800 news sentences annotated for subjectivity — whether the sentence expresses opinions (SUBJ) or facts (OBJ). Suitable for subjectivity detection, opinion mining, NLP classification, news objectivity analysis, multilingual text classification.

800 records2025

CLEF CheckThat! 2023 Subjectivity — German Analyzed

A CLEF CheckThat! 2023 subjectivity task (german) dataset of 800 sentences with subjectivity labels (38.5% subjective), collected by CLEF CheckThat! Lab organizers (2023). Each record contains sentence text, binary subjectivity label (SUBJ/OBJ), sentence ID, conflict resolution flag. CLEF 2023 CheckThat! subjectivity (german) provides 800 news sentences annotated for subjectivity — whether the sentence expresses opinions (SUBJ) or facts (OBJ). Suitable for subjectivity detection, opinion mining, NLP classification, news objectivity analysis, multilingual text classification.

800 records2023

CLEF CheckThat! 2023 Subjectivity — Dutch Analyzed

A CLEF CheckThat! 2023 subjectivity task (dutch) dataset of 800 sentences with subjectivity labels (38.9% subjective), collected by CLEF CheckThat! Lab organizers (2023). Each record contains sentence text, binary subjectivity label (SUBJ/OBJ), sentence ID, conflict resolution flag. CLEF 2023 CheckThat! subjectivity (dutch) provides 800 news sentences annotated for subjectivity — whether the sentence expresses opinions (SUBJ) or facts (OBJ). Suitable for subjectivity detection, opinion mining, NLP classification, news objectivity analysis, multilingual text classification.

800 records2023

CLEF CheckThat! 2023 Subjectivity — Turkish Analyzed

A CLEF CheckThat! 2023 subjectivity task (turkish) dataset of 800 sentences with subjectivity labels (47.2% subjective), collected by CLEF CheckThat! Lab organizers (2023). Each record contains sentence text, binary subjectivity label (SUBJ/OBJ), sentence ID, conflict resolution flag. CLEF 2023 CheckThat! subjectivity (turkish) provides 800 news sentences annotated for subjectivity — whether the sentence expresses opinions (SUBJ) or facts (OBJ). Suitable for subjectivity detection, opinion mining, NLP classification, news objectivity analysis, multilingual text classification.

800 records2023

CLEF CheckThat! 2024 Subjectivity — German Analyzed

A CLEF CheckThat! 2024 subjectivity task (german) dataset of 800 sentences with subjectivity labels (38.5% subjective), collected by CLEF CheckThat! Lab organizers (2024). Each record contains sentence text, binary subjectivity label (SUBJ/OBJ), sentence ID, conflict resolution flag. CLEF 2024 CheckThat! subjectivity (german) provides 800 news sentences annotated for subjectivity — whether the sentence expresses opinions (SUBJ) or facts (OBJ). Suitable for subjectivity detection, opinion mining, NLP classification, news objectivity analysis, multilingual text classification.

800 records2024

CLEF CheckThat! 2024 Subjectivity — Bulgarian Analyzed

A CLEF CheckThat! 2024 subjectivity task (bulgarian) dataset of 691 sentences with subjectivity labels (45.2% subjective), collected by CLEF CheckThat! Lab organizers (2024). Each record contains sentence text, binary subjectivity label (SUBJ/OBJ), sentence ID, conflict resolution flag. CLEF 2024 CheckThat! subjectivity (bulgarian) provides 691 news sentences annotated for subjectivity — whether the sentence expresses opinions (SUBJ) or facts (OBJ). Suitable for subjectivity detection, opinion mining, NLP classification, news objectivity analysis, multilingual text classification.

691 records2024

CLEF CheckThat! 2025 Subjectivity — Bulgarian Analyzed

A CLEF CheckThat! 2025 subjectivity task (bulgarian) dataset of 691 sentences with subjectivity labels (45.2% subjective), collected by CLEF CheckThat! Lab organizers (2025). Each record contains sentence text, binary subjectivity label (SUBJ/OBJ), sentence ID, conflict resolution flag. CLEF 2025 CheckThat! subjectivity (bulgarian) provides 691 news sentences annotated for subjectivity — whether the sentence expresses opinions (SUBJ) or facts (OBJ). Suitable for subjectivity detection, opinion mining, NLP classification, news objectivity analysis, multilingual text classification.

691 records2025

Wikipedia Hoax and Non-Hoax Articles Analyzed

Wikipedia hoax and non-hoax articles from Kumar, West & Leskovec, 'Disinformation on the Web' (WWW 2016), distributed by SNAP. The README describes 64 hoaxes, each paired with a non-hoax article created the same day with similar appearance; the parsed folders hold those 64 + 64 articles, while the cleaned-markup folder holds 76 hoaxes and 64 non-hoaxes (140 articles). The archive is SNAP's own and also contains 65 macOS '._' resource-fork files, which are not articles. Released under the CRAPL licence (CRAPL-LICENSE.txt is included).

140 records2016

US Attention Data (2020-2025) Analyzed

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.

51 records2026