Maarten Sap

6.2k citations
70 papers · 2.9k indexed · 3 hit papers · h-index 25

Maarten Sap

60 papers receiving 2.7k citations

Hit Papers

The Risk of Racial Bias in Hate Speech Detection4172015202620182022100200300400

Peers

Maarten Sap
Comparison fields: 5 of 115
  • Artificial Intelligence 1.9k
  • Applied Psychology 279
  • Health Informatics 48
  • Social Psychology 705
  • Communication 202
Replace Daniel Preoțiuc-Pietro with:
Daniel Preoțiuc-Pietro United States
Gregory Park United States
Stevie Chancellor United States
Jamie Guillory United States
Lukasz Dziurzynski United States
Koustuv Saha United States
Megha Agrawal India
Dirk Hovy Italy
Michael Gamon United States
David Milne Australia
Maarten Sap relative to Daniel Preoțiuc-Pietro United States Daniel Preoțiuc-Pietro's profile →
Citations per field
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Daniel Preoțiuc-Pietro · 1×
Citations per year

Countries citing papers authored by Maarten Sap

Since Specialization
Citations

This map shows the geographic impact of Maarten Sap's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Maarten Sap with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maarten Sap more than expected).

Fields of papers citing papers by Maarten Sap

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maarten Sap. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Maarten Sap. The network helps show where Maarten Sap may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Maarten Sap, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Maarten Sap Line = papers co-authored together Maarten Sap links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20240
4 20241
5 20241
6 20231
7 20232
8 20239
9 202257
10 20222
11 202212
12 202291
13 202135
14
On-the-Fly Controlled Text Generation with Experts and Anti-Experts.
20215
15 202194
16 202029
17
COMET: Commonsense Transformers for Automatic Knowledge Graph Constructionbreakdown →
2019464
18
COMET: Commonsense Transformers for Knowledge Graph Construction
20198
19 2016139
20 201595

About Maarten Sap

Maarten Sap is a scholar working on Artificial Intelligence, General Social Sciences, Safety Research, Applied Psychology and Social Psychology, having authored 70 papers that have together received 2.9k indexed citations. Recurring topics across this work include Topic Modeling (22 papers), Natural Language Processing Techniques (18 papers), Hate Speech and Cyberbullying Detection (15 papers), Mental Health via Writing (9 papers), Ethics and Social Impacts of AI (7 papers), Misinformation and Its Impacts (7 papers), Speech and dialogue systems (5 papers) and Sentiment Analysis and Opinion Mining (4 papers). The work is most often cited by research in Artificial Intelligence (1.9k citations), Applied Psychology (279 citations), Health Informatics (48 citations), Social Psychology (705 citations) and Communication (202 citations). Maarten Sap has collaborated with scholars based in United States, United Kingdom and Australia. Frequent co-authors include Yejin Choi, Lyle Ungar, Noah A. Smith, Johannes C. Eichstaedt, Gregory Park, Margaret L. Kern, Hannah Rashkin, H. Andrew Schwartz, Saadia Gabriel and Antoine Bosselut. Their work appears in journals such as JMIR Mental Health, Nature Machine Intelligence, Journal of Medical Internet Research, Psychological Methods and Journal of Personality.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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