MétaCan
Menu
Cohort builder

4,299,418 works, Canadian by any of four routes.

Every filter state is a URL; the URL is the query; the query is citable via /q/⟨hash⟩. The page, the API and the export parse the same parameters.

The current cohort, streamed from the database: every work column, the machine labels, the provisional scores, and the per-row validation status. Exports are capped at 100,000 rows. Mints a permanent /q/ link for this exact query. The same filters always produce the same link, whoever asks.

Search term
Author
Year range
Sort
Language
Type
Field
Venue
Topic
Sentiment Analysis and Opinion Mining
Retraction
Abstract
Evidence source
Study design
Label agreement
Label status

Direct Codex and Gemma labels are unvalidated and sparse. Distilled predictions cover the full frame and are also unvalidated. Choose the evidence source explicitly; absence of a direct label is never a negative label.

affaffiliation
fundfunder
venuejournal
aboutaboutness

The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

797 results · 1 filter active ·
Results by year
20002025
Publication date
Categories
Machine labels · sparse coverage
Evidence
Language
Type
Citations
An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
797 works in the cohort · of 4,299,418page 1 of 16

Labels cover 0 of 797 works in this cohort. The rest are unlabeled, which is not a negative label: the label table is sparse today and grows as labeling rounds land.

Distilled predictions cover 797 of 797 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

afffundunlabeled
Lexicon-Based Methods for Sentiment Analysis
Maite Taboada, Julian Brooke, Milan Tofiloski, Kimberly Voll, Manfred Stede
2011· article· en· Computational Linguistics· Computer Science
distilled prediction:candidate · noneconsensus · none
3,255
citations
affunlabeled
Measuring praise and criticism
Peter D. Turney, Michael L. Littman
2003· article· en· ACM Transactions on Information Systems· Computer Science
distilled prediction:candidate · noneconsensus · none
1,509
citations
affunlabeled
Sentiment Analysis of Short Informal Texts
Svetlana Kiritchenko, Xiaodan Zhu, Seyed Mohammad
2014· article· en· Journal of Artificial Intelligence Research· Computer Science
distilled prediction:candidate · noneconsensus · none
890
citations
affunlabeled
SemEval-2016 Task 6: Detecting Stance in Tweets
Saif M. Mohammad, Svetlana Kiritchenko, Parinaz Sobhani, Xiaodan Zhu, Colin Cherry
2016· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
857
citations
affunlabeled
SemEval-2018 Task 1: Affect in Tweets
Saif M. Mohammad, Felipe Bravo-Márquez, Mohammad Salameh, Svetlana Kiritchenko
2018· article· en· Computer Science
distilled prediction:candidate · insufficient_payloadconsensus · none
745
citations
affunlabeled
Stance and Sentiment in Tweets
Saif M. Mohammad, Parinaz Sobhani, Svetlana Kiritchenko
2017· article· en· ACM Transactions on Internet Technology· Computer Science
distilled prediction:candidate · noneconsensus · none
435
citations
affno abstractunlabeled
Sentiment Analysis
Saif M. Mohammad
2016· book-chapter· en· Elsevier eBooks· Computer Science
distilled prediction:candidate · metaepi_narrow+insufficient_payloadconsensus · insufficient_payload
384
citations
afffundunlabeled
SemEval-2015 Task 10: Sentiment Analysis in Twitter
Sara Rosenthal, Preslav Nakov, Svetlana Kiritchenko, Saif M. Mohammad, Alan Ritter, Veselin Stoyanov
2015· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
367
citations
affunlabeled
ARSA
Yang Liu, Aijun An, Xiaohui Yu
2007· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
309
citations
affunlabeled
Emotional Tweets
Saif M. Mohammad
2012· article· en· Joint Conference on Lexical and Computational Semantics· Computer Science
distilled prediction:candidate · noneconsensus · none
300
citations
affunlabeled
WASSA-2017 shared task on emotion intensity
Felipe Bravo-Márquez
2019· article· en· Research Commons (University of Waikato)· Computer Science
distilled prediction:candidate · insufficient_payloadconsensus · none
264
citations
affunlabeled
ILDA
Samaneh Moghaddam, Martin Ester
2011· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
202
citations
affunlabeled
How Translation Alters Sentiment
Saif M. Mohammad, Mohammad Salameh, Svetlana Kiritchenko
2016· article· en· Journal of Artificial Intelligence Research· Computer Science
distilled prediction:candidate · noneconsensus · none
194
citations
affunlabeled
Opinion digger
Samaneh Moghaddam, Martin Ester
2010· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
194
citations
fundno affunlabeled
Refining Word Embeddings for Sentiment Analysis
Liang-Chih Yu, Jin Wang, K. Robert Lai, Xuejie Zhang
2017· article· en· Computer Science
distilled prediction:candidate · scholarly_communicationconsensus · none
190
citations
affunlabeled
Analyzing Appraisal Automatically
Maite Taboada, Jack Grieve
2004· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
180
citations

How this was built: Screen · Findings · About