Tae Yano

458 total citations
16 papers, 250 citations indexed

About

Tae Yano is a scholar working on Artificial Intelligence, General Social Sciences and Information Systems. According to data from OpenAlex, Tae Yano has authored 16 papers receiving a total of 250 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 4 papers in General Social Sciences and 3 papers in Information Systems. Recurrent topics in Tae Yano's work include Topic Modeling (8 papers), Computational and Text Analysis Methods (4 papers) and Sentiment Analysis and Opinion Mining (3 papers). Tae Yano is often cited by papers focused on Topic Modeling (8 papers), Computational and Text Analysis Methods (4 papers) and Sentiment Analysis and Opinion Mining (3 papers). Tae Yano collaborates with scholars based in United States and United Kingdom. Tae Yano's co-authors include Noah A. Smith, Noah A. Smith, William W. Cohen, John Wilkerson, Daniel Preoțiuc-Pietro, Justin Cranshaw, Patrick Pantel, Michael Gamon, Xinying Song and Philip Resnik and has published in prestigious journals such as Language Resources and Evaluation, Figshare and Columbia Academic Commons (Columbia University).

In The Last Decade

Tae Yano

14 papers receiving 231 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tae Yano United States	7	170	59	55	40	32	16	250
Manar Alkhatib United Arab Emirates	8	125 0.7×	28 0.5×	33 0.6×	53 1.3×	23 0.7×	27	232
Mikalai Tsytsarau Italy	6	277 1.6×	69 1.2×	97 1.8×	63 1.6×	25 0.8×	11	366
Ting Hua United States	8	122 0.7×	91 1.5×	66 1.2×	61 1.5×	30 0.9×	12	233
Haishen Yao China	6	183 1.1×	24 0.4×	58 1.1×	34 0.8×	10 0.3×	10	248
Martin Saveski United States	7	102 0.6×	34 0.6×	124 2.3×	40 1.0×	24 0.8×	14	246
Diego Sáez-Trumper Spain	11	112 0.7×	110 1.9×	91 1.7×	147 3.7×	121 3.8×	29	390
Danish Contractor India	10	242 1.4×	97 1.6×	81 1.5×	19 0.5×	23 0.7×	27	343
Steven Van Canneyt Belgium	9	136 0.8×	40 0.7×	56 1.0×	38 0.9×	13 0.4×	13	243
Anjie Fang United States	11	292 1.7×	27 0.5×	18 0.3×	29 0.7×	31 1.0×	19	356
Zhunchen Luo China	9	199 1.2×	52 0.9×	74 1.3×	39 1.0×	19 0.6×	23	290

Countries citing papers authored by Tae Yano

Since Specialization

Citations

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

Fields of papers citing papers by Tae Yano

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tae Yano

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

All Works

Sort: Min cites: Since: Top N: Style:

16 of 16 papers shown

Yano, Tae. (2025). Text as Actuator: Text-Driven Response Modeling and Prediction in Politics. Figshare.

Yano, Tae, Dani Yogatama, & Noah A. Smith. (2021). A Penny for Your Tweets: Campaign Contributions and Capitol Hill Microblogs. Proceedings of the International AAAI Conference on Web and Social Media. 7(1). 737–740. 1 indexed citations

Yano, Tae, et al.. (2020). Deep Neural Query Understanding System at Expedia Group. 32. 1476–1484.

Eisenstein, Jacob, Tae Yano, William W. Cohen, Noah A. Smith, & Eric P. Xing. (2018). Structured Databases of Named Entities from Bayesian Nonparametrics. Figshare. 2–12. 1 indexed citations

Yano, Tae, Philip Resnik, & Noah A. Smith. (2018). Shedding (a Thousand Points of) Light on Biased Language. Research Showcase @ Carnegie Mellon University (Carnegie Mellon University). 18 indexed citations

Yano, Tae, Noah A. Smith, & John Wilkerson. (2018). Textual Predictors of Bill Survival in Congressional Committees. Research Showcase @ Carnegie Mellon University (Carnegie Mellon University). 793–802. 23 indexed citations

Gamon, Michael, Tae Yano, Xinying Song, & Patrick Pantel. (2013). Understanding Document Aboutness Step One: Identifying Salient Entities. 5 indexed citations

Gamon, Michael, Tae Yano, Xinying Song, Johnson Apacible, & Patrick Pantel. (2013). Identifying salient entities in web pages. 2375–2380. 23 indexed citations

Preoțiuc-Pietro, Daniel, Justin Cranshaw, & Tae Yano. (2013). Exploring venue-based city-to-city similarity measures. 1–4. 21 indexed citations

10.

Yano, Tae & Noah A. Smith. (2010). What’s Worthy of Comment? Content and Comment Volume in Political Blogs. Proceedings of the International AAAI Conference on Web and Social Media. 4(1). 359–362. 70 indexed citations

11.

Yano, Tae, William W. Cohen, & Noah A. Smith. (2009). Predicting response to political blog posts with topic models. 477–477. 75 indexed citations

12.

Passonneau, Rebecca J., et al.. (2008). Relation between Agreement Measures on Human Labeling and Machine Learning Performance: Results from an Art History Domain. Language Resources and Evaluation. 2841–2848. 6 indexed citations

13.

Passonneau, Rebecca J., Tae Yano, & Judith L. Klavans. (2008). Functional semantic categories for art history text: human labeling and preliminary machine learning. 1 indexed citations

14.

Klavans, Judith L., Eileen G. Abels, Jimmy Lin, et al.. (2008). Computational linguistics for metadata building: Aggregating text processing technologies for enhanced image access. DigitalCommons - WayneState (Wayne State University). 1 indexed citations

15.

Passonneau, Rebecca J., et al.. (2008). Functional Semantic Categories for Art History Text - Human Labeling and Preliminary Machine Learning. 13–22. 4 indexed citations

16.

Passonneau, Rebecca J., et al.. (2007). Selecting and Categorizing Textual Descriptions of Images in the Context of an Image Indexer's Toolkit. Columbia Academic Commons (Columbia University). 1 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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