Lucy Vasserman

1.2k total citations · 1 hit paper
8 papers, 635 citations indexed

About

Lucy Vasserman is a scholar working on Artificial Intelligence, Communication and Sociology and Political Science. According to data from OpenAlex, Lucy Vasserman has authored 8 papers receiving a total of 635 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 1 paper in Communication and 1 paper in Sociology and Political Science. Recurrent topics in Lucy Vasserman's work include Hate Speech and Cyberbullying Detection (5 papers), Topic Modeling (3 papers) and Natural Language Processing Techniques (3 papers). Lucy Vasserman is often cited by papers focused on Hate Speech and Cyberbullying Detection (5 papers), Topic Modeling (3 papers) and Natural Language Processing Techniques (3 papers). Lucy Vasserman collaborates with scholars based in United States. Lucy Vasserman's co-authors include Jeffrey Sorensen, Nithum Thain, Lucas Dixon, John Li, Nitesh Goyal, Alyssa Lees, Vinh Q. Tran, Jai Prakash Gupta, Yi Tay and Donald Metzler and has published in prestigious journals such as Proceedings of the ACM on Human-Computer Interaction, CHI Conference on Human Factors in Computing Systems and Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.

In The Last Decade

Lucy Vasserman

7 papers receiving 599 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Measuring and Mitigating Unintended Bias in Text Classification

2018 338 citations Lucas Dixon, John Li et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Lucy Vasserman United States	7	529	100	83	80	66	8	635
Prasenjit Majumder India	14	821 1.6×	40 0.4×	21 0.3×	208 2.6×	73 1.1×	68	905
Florian Lemmerich Germany	10	140 0.3×	104 1.0×	9 0.1×	89 1.1×	94 1.4×	41	356
Alexandra Schofield United States	8	155 0.3×	69 0.7×	11 0.1×	34 0.4×	47 0.7×	13	310
Alon Jacovi Israel	7	348 0.7×	40 0.4×	146 1.8×	67 0.8×	5 0.1×	11	507
Esin Durmus United States	10	280 0.5×	45 0.5×	40 0.5×	32 0.4×	20 0.3×	18	432
Marcin Gruza Poland	8	405 0.8×	62 0.6×	28 0.3×	48 0.6×	20 0.3×	13	581
Vidya Rajaram United States	4	149 0.3×	26 0.3×	29 0.3×	57 0.7×	13 0.2×	6	295
Maxim Mozgovoy Japan	12	241 0.5×	40 0.4×	100 1.2×	141 1.8×	8 0.1×	50	464
Dolf Trieschnigg Netherlands	14	472 0.9×	46 0.5×	7 0.1×	216 2.7×	42 0.6×	44	654
Besnik Fetahu Germany	13	450 0.9×	53 0.5×	17 0.2×	80 1.0×	39 0.6×	41	566

Countries citing papers authored by Lucy Vasserman

Since Specialization

Citations

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

Fields of papers citing papers by Lucy Vasserman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lucy Vasserman. 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 Lucy Vasserman. The network helps show where Lucy Vasserman may publish in the future.

Co-authorship network of co-authors of Lucy Vasserman

This figure shows the co-authorship network connecting the top 25 collaborators of Lucy Vasserman. A scholar is included among the top collaborators of Lucy Vasserman 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 Lucy Vasserman. Lucy Vasserman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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8 of 8 papers shown

1.

Goyal, Nitesh, Ian Kivlichan, Rachel Rosen, & Lucy Vasserman. (2022). Is Your Toxicity My Toxicity? Exploring the Impact of Rater Identity on Toxicity Annotation. Proceedings of the ACM on Human-Computer Interaction. 6(CSCW2). 1–28. 37 indexed citations

2.

Lees, Alyssa, Vinh Q. Tran, Yi Tay, et al.. (2022). A New Generation of Perspective API: Efficient Multilingual Character-level Transformers. Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 3197–3207. 67 indexed citations

3.

Lees, Alyssa, et al.. (2022). Lost in Distillation: A Case Study in Toxicity Modeling. 92–101.

4.

Goyal, Nitesh, et al.. (2022). ”You have to prove the threat is real”: Understanding the needs of Female Journalists and Activists to Document and Report Online Harassment. CHI Conference on Human Factors in Computing Systems. 1–17. 21 indexed citations

5.

Dixon, Lucas, et al.. (2019). Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification. 491–500. 149 indexed citations

6.

Dixon, Lucas, John Li, Jeffrey Sorensen, Nithum Thain, & Lucy Vasserman. (2018). Measuring and Mitigating Unintended Bias in Text Classification. 67–73. 338 indexed citations breakdown →

7.

Vasserman, Lucy, et al.. (2016). Contextual language model adaptation using dynamic classes. 18. 441–446. 12 indexed citations

8.

Vasserman, Lucy, et al.. (2015). Sequence-based class tagging for robust transcription in ASR. 473–477. 11 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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