Ryen W. White

18.5k total citations · 2 hit papers
255 papers, 9.1k citations indexed

About

Ryen W. White is a scholar working on Information Systems, Artificial Intelligence and Computer Science Applications. According to data from OpenAlex, Ryen W. White has authored 255 papers receiving a total of 9.1k indexed citations (citations by other indexed papers that have themselves been cited), including 163 papers in Information Systems, 83 papers in Artificial Intelligence and 44 papers in Computer Science Applications. Recurrent topics in Ryen W. White's work include Information Retrieval and Search Behavior (138 papers), Web Data Mining and Analysis (71 papers) and Expert finding and Q&A systems (60 papers). Ryen W. White is often cited by papers focused on Information Retrieval and Search Behavior (138 papers), Web Data Mining and Analysis (71 papers) and Expert finding and Q&A systems (60 papers). Ryen W. White collaborates with scholars based in United States, United Kingdom and Switzerland. Ryen W. White's co-authors include Eric Horvitz, Susan Dumais, Resa A. Roth, Jeff Huang, Steven M. Drucker, Paul N. Bennett, Ian Ruthven, Joemon M. Jose, Jaime Teevan and Gary Marchionini and has published in prestigious journals such as Nature Communications, Communications of the ACM and Computer.

In The Last Decade

Ryen W. White

248 papers receiving 8.7k citations

Hit Papers

Exploratory Search: Beyond the Query-Response Paradigm 2009 2026 2014 2020 2009 2016 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ryen W. White United States 52 5.2k 2.7k 1.3k 1.2k 1.0k 255 9.1k
Peter Pirolli United States 46 3.2k 0.6× 2.5k 0.9× 1.8k 1.4× 1.6k 1.4× 951 0.9× 137 9.6k
Amanda Spink United States 47 6.4k 1.2× 2.8k 1.0× 1.3k 1.0× 915 0.8× 440 0.4× 224 9.6k
Jaime Teevan United States 43 3.7k 0.7× 2.5k 0.9× 1.1k 0.9× 792 0.7× 1.3k 1.3× 152 7.8k
Gary Marchionini United States 36 3.7k 0.7× 1.9k 0.7× 1.0k 0.8× 1.5k 1.2× 695 0.7× 194 7.2k
Loren Terveen United States 47 5.2k 1.0× 2.8k 1.0× 2.1k 1.6× 1.6k 1.4× 1.5k 1.4× 174 10.5k
Nicholas J. Belkin United States 38 4.6k 0.9× 2.7k 1.0× 683 0.5× 755 0.6× 581 0.6× 175 6.9k
Ed H. United States 49 3.8k 0.7× 3.3k 1.2× 1.8k 1.4× 1.8k 1.5× 1.9k 1.8× 174 9.8k
John Grundy Australia 46 5.6k 1.1× 2.7k 1.0× 395 0.3× 671 0.6× 732 0.7× 574 9.0k
Geri Gay United States 46 2.1k 0.4× 1.1k 0.4× 2.0k 1.5× 799 0.7× 701 0.7× 145 7.8k
Francesco Ricci⋆ Italy 37 6.8k 1.3× 3.5k 1.3× 1.6k 1.2× 2.5k 2.1× 587 0.6× 214 9.6k

Countries citing papers authored by Ryen W. White

Since Specialization
Citations

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

Fields of papers citing papers by Ryen W. White

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ryen W. White. 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 Ryen W. White. The network helps show where Ryen W. White may publish in the future.

Co-authorship network of co-authors of Ryen W. White

This figure shows the co-authorship network connecting the top 25 collaborators of Ryen W. White. A scholar is included among the top collaborators of Ryen W. White 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 Ryen W. White. Ryen W. White 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.
Shah, Chirag, Ryen W. White, Reid Andersen, et al.. (2025). Using Large Language Models to Generate, Validate, and Apply User Intent Taxonomies. ACM Transactions on the Web. 19(3). 1–29. 3 indexed citations
2.
Nath, Suman, et al.. (2025). From Search Engines to Action Engines. Computer. 58(6). 59–68. 1 indexed citations
3.
Gligorić, Kristina, Arnaud Chioléro, Emre Kıcıman, et al.. (2024). Food choice mimicry on a large university campus. PNAS Nexus. 3(12). pgae517–pgae517.
4.
Wan, Mengting, Tara Safavi, Siddharth Suri, et al.. (2024). TnT-LLM: Text Mining at Scale with Large Language Models. 5836–5847. 15 indexed citations
5.
Shah, Chirag, et al.. (2023). Taking Search to Task. 1–13. 11 indexed citations
6.
Rahaman, Mohammad Saiedur, Johanne R. Trippas, Damiano Spina, et al.. (2022). Imagining future digital assistants at work: A study of task management needs. International Journal of Human-Computer Studies. 168. 102905–102905. 4 indexed citations
7.
Trippas, Johanne R., Damiano Spina, Mohammad Saiedur Rahaman, et al.. (2019). Building a Benchmark for Task Progress in Digital Assistants. RMIT Research Repository (RMIT University Library). 2 indexed citations
8.
Farajtabar, Mehrdad, et al.. (2018). Modeling behaviors and lifestyle with online and social data for predicting and analyzing sleep and exercise quality. International Journal of Data Science and Analytics. 8(4). 367–383. 5 indexed citations
9.
Bennett, Paul N. & Ryen W. White. (2015). Mining Tasks from the Web Anchor Text Graph: MSR Notebook Paper for the TREC 2015 Tasks Track. Text REtrieval Conference. 1 indexed citations
10.
Cooper, Kathryn E., et al.. (2014). “THICK” NARRATIVES: MINING IMPLICIT, OBLIQUE, AND DEEPER UNDERSTANDINGS IN VIDEOTAPED RESEARCH DATA. INTED2014 Proceedings. 6772–6778. 1 indexed citations
11.
Guo, Qi, et al.. (2011). Why users switch: Understanding and predicting search engine switching rationales. International ACM SIGIR Conference on Research and Development in Information Retrieval. 1 indexed citations
12.
Kotov, Alexander, Paul N. Bennett, Ryen W. White, Susan Dumais, & Jaime Teevan. (2011). Modeling and Analyses of Multi-Session Search Tasks. International ACM SIGIR Conference on Research and Development in Information Retrieval. 2 indexed citations
13.
Lynch, Karen, et al.. (2010). Pushing Content to Mobile Phones: What do Students Want?. USC Research Bank (University of the Sunshine Coast). 2 indexed citations
14.
Macdonald, Craig, Iadh Ounis, Vassilis Plachouras, Ian Ruthven, & Ryen W. White. (2008). Advances in information retrieval : 30th European Conference on IR Research, ECIR 2008, Glasgow, UK, March 30-April 3, 2008 : proceedings. DIAL (Catholic University of Leuven). 5 indexed citations
15.
Edmonds, Andy, Ryen W. White, Dan Morris, & Steven M. Drucker. (2007). Instrumenting the dynamic web. Journal of Web Engineering. 6(3). 244–260. 10 indexed citations
16.
White, Ryen W., Bill Kules, Steven M. Drucker, & m.c. schraefel. (2006). Supporting exploratory search. Communications of the ACM. 49(4). 36–39. 130 indexed citations
17.
White, Ryen W.. (2004). A Visualisation Technique to Communicate Implicit Feedback Decisions. 2 indexed citations
18.
White, Ryen W., Joemon M. Jose, & Ian Ruthven. (2003). Using Top-Ranking Sentences for Web Search Result Presentation.. 1 indexed citations
19.
Ounis, Iadh, et al.. (2002). Using Hierarchical Clustering and Summarisation Approaches for Web Retrieval: Glasgow at the TREC 2002 Interactive Track.. Text REtrieval Conference. 12 indexed citations
20.
White, Ryen W., Joemon M. Jose, & Ian Ruthven. (2002). Comparing explicit and implicit feedback techniques for Web retrieval: TREC-10 interactive track report. Strathprints: The University of Strathclyde institutional repository (University of Strathclyde). 534–538. 27 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026