Su Lin Blodgett

762 total citations
23 papers, 230 citations indexed

About

Su Lin Blodgett is a scholar working on Artificial Intelligence, Information Systems and Safety Research. According to data from OpenAlex, Su Lin Blodgett has authored 23 papers receiving a total of 230 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 4 papers in Information Systems and 4 papers in Safety Research. Recurrent topics in Su Lin Blodgett's work include Topic Modeling (9 papers), Natural Language Processing Techniques (8 papers) and Hate Speech and Cyberbullying Detection (5 papers). Su Lin Blodgett is often cited by papers focused on Topic Modeling (9 papers), Natural Language Processing Techniques (8 papers) and Hate Speech and Cyberbullying Detection (5 papers). Su Lin Blodgett collaborates with scholars based in United States, United Kingdom and Canada. Su Lin Blodgett's co-authors include Hanna Wallach, Alexandra Olteanu, Robert B. Sim, Brendan O’Connor, Johnny Tian-Zheng Wei, Hal Daumé, Solon Barocas, Morgan Klaus Scheuerman, Adam Trischler and Angelina Wang and has published in prestigious journals such as Nature, Proceedings of the ACM on Human-Computer Interaction and NPARC.

In The Last Decade

Su Lin Blodgett

19 papers receiving 226 citations

Peers

Su Lin Blodgett
Kamrun Naher Keya United States
Rashidul Islam United States
Joe Barrow United States
Shrimai Prabhumoye United States
Myra Cheng United States
Paul Röttger United Kingdom
Hila Gonen United States
Isabel O. Gallegos United States
Marcelo Prates Brazil
Kawin Ethayarajh United States
Kamrun Naher Keya United States
Su Lin Blodgett
Citations per year, relative to Su Lin Blodgett Su Lin Blodgett (= 1×) peers Kamrun Naher Keya

Countries citing papers authored by Su Lin Blodgett

Since Specialization
Citations

This map shows the geographic impact of Su Lin Blodgett'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 Su Lin Blodgett with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Su Lin Blodgett more than expected).

Fields of papers citing papers by Su Lin Blodgett

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Su Lin Blodgett. 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 Su Lin Blodgett. The network helps show where Su Lin Blodgett may publish in the future.

Co-authorship network of co-authors of Su Lin Blodgett

This figure shows the co-authorship network connecting the top 25 collaborators of Su Lin Blodgett. A scholar is included among the top collaborators of Su Lin Blodgett based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Su Lin Blodgett. Su Lin Blodgett is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Blodgett, Su Lin, et al.. (2025). Dehumanizing Machines: Mitigating Anthropomorphic Behaviors in Text Generation Systems. 25923–25948. 2 indexed citations
2.
Nozza, Debora, et al.. (2024). Metrics for What, Metrics for Whom: Assessing Actionability of Bias Evaluation Metrics in NLP. 21669–21691. 1 indexed citations
3.
Blodgett, Su Lin, et al.. (2024). ECBD: Evidence-Centered Benchmark Design for NLP. 16349–16365. 1 indexed citations
4.
Lucy, Li, Su Lin Blodgett, Milad Shokouhi, Hanna Wallach, & Alexandra Olteanu. (2024). “One-Size-Fits-All”? Examining Expectations around What Constitute “Fair” or “Good” NLG System Behaviors. 1054–1089.
5.
Blodgett, Su Lin & Zeerak Talat. (2024). LLMs produce racist output when prompted in African American English. Nature. 633(8028). 40–41.
6.
Blodgett, Su Lin, et al.. (2024). The Perspectivist Paradigm Shift: Assumptions and Challenges of Capturing Human Labels. 2279–2292. 2 indexed citations
7.
8.
Blodgett, Su Lin, et al.. (2023). This prompt is measuring <mask>: evaluating bias evaluation in language models. NPARC. 2209–2225. 3 indexed citations
9.
Blodgett, Su Lin, et al.. (2023). FairPrism: Evaluating Fairness-Related Harms in Text Generation. 6231–6251. 5 indexed citations
10.
Yuan, Xingdi, et al.. (2023). It Takes Two to Tango: Navigating Conceptualizations of NLP Tasks and Measurements of Performance. 3234–3279. 2 indexed citations
11.
Katzman, Jared, Angelina Wang, Morgan Klaus Scheuerman, et al.. (2023). Taxonomizing and Measuring Representational Harms: A Look at Image Tagging. Proceedings of the AAAI Conference on Artificial Intelligence. 37(12). 14277–14285. 12 indexed citations
12.
Cao, Meng, et al.. (2023). Responsible AI Considerations in Text Summarization Research: A Review of Current Practices. 6246–6261. 2 indexed citations
13.
14.
Gupta, Ankita, Su Lin Blodgett, Justin H. Gross, & Brendan O’Connor. (2022). Examining Political Rhetoric with Epistemic Stance Detection. 89–104.
15.
Blodgett, Su Lin, et al.. (2022). Examining Responsibility and Deliberation in AI Impact Statements and Ethics Reviews. 424–435. 6 indexed citations
16.
Zhou, Kaitlyn, Su Lin Blodgett, Adam Trischler, et al.. (2022). Deconstructing NLG Evaluation: Evaluation Practices, Assumptions, and Their Implications. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 12 indexed citations
17.
Blodgett, Su Lin, Q. Vera Liao, Alexandra Olteanu, et al.. (2022). Responsible Language Technologies: Foreseeing and Mitigating Harms. CHI Conference on Human Factors in Computing Systems Extended Abstracts. 1–3. 14 indexed citations
18.
Blodgett, Su Lin, et al.. (2021). Stereotyping Norwegian Salmon: An Inventory of Pitfalls in Fairness Benchmark Datasets. 1004–1015. 96 indexed citations
19.
Jacobs, Abigail Z., Su Lin Blodgett, Solon Barocas, Hal Daumé, & Hanna Wallach. (2020). The meaning and measurement of bias. 706–706. 12 indexed citations
20.
Blodgett, Su Lin, Johnny Tian-Zheng Wei, & Brendan O’Connor. (2017). A Dataset and Classifier for Recognizing Social Media English. 7 indexed citations

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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2026