Varada Kolhatkar

440 total citations
13 papers, 239 citations indexed

About

Varada Kolhatkar is a scholar working on Artificial Intelligence, Information Systems and Communication. According to data from OpenAlex, Varada Kolhatkar has authored 13 papers receiving a total of 239 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 3 papers in Information Systems and 1 paper in Communication. Recurrent topics in Varada Kolhatkar's work include Topic Modeling (8 papers), Speech and dialogue systems (5 papers) and Natural Language Processing Techniques (5 papers). Varada Kolhatkar is often cited by papers focused on Topic Modeling (8 papers), Speech and dialogue systems (5 papers) and Natural Language Processing Techniques (5 papers). Varada Kolhatkar collaborates with scholars based in Canada, Germany and United States. Varada Kolhatkar's co-authors include Maite Taboada, Ted Pedersen, Graeme Hirst, Heike Zinsmeister, Stefanie Dipper, Liam Peyton, Debbie S. Gipson, Khaled El Emam, Andrew S. Cassidy and Elmar Nöth and has published in prestigious journals such as Journal of Biomedical Informatics, Computational Linguistics and First Monday.

In The Last Decade

Varada Kolhatkar

13 papers receiving 222 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Varada Kolhatkar Canada	10	203	28	24	19	18	13	239
E.F. Tjong Kim Sang Netherlands	7	237 1.2×	14 0.5×	33 1.4×	20 1.1×	4 0.2×	23	296
Anna Feldman United States	11	301 1.5×	14 0.5×	31 1.3×	22 1.2×	9 0.5×	44	338
Anna Gladkova Japan	7	222 1.1×	15 0.5×	11 0.5×	15 0.8×	5 0.3×	9	291
Aasish Pappu United States	8	168 0.8×	31 1.1×	44 1.8×	19 1.0×	4 0.2×	29	217
Kalliopi Zervanou Netherlands	8	163 0.8×	8 0.3×	34 1.4×	16 0.8×	7 0.4×	31	209
Tamás Váradi Hungary	9	177 0.9×	9 0.3×	21 0.9×	7 0.4×	13 0.7×	32	271
Alessio Palmero Aprosio Italy	7	169 0.8×	14 0.5×	23 1.0×	16 0.8×	4 0.2×	25	187
Leonid Boytsov United States	6	196 1.0×	15 0.5×	44 1.8×	43 2.3×	6 0.3×	11	261
Shu‐Kai Hsieh Taiwan	7	184 0.9×	7 0.3×	18 0.8×	10 0.5×	6 0.3×	52	237
Martin Reynaert Netherlands	8	205 1.0×	7 0.3×	24 1.0×	51 2.7×	26 1.4×	24	255

Countries citing papers authored by Varada Kolhatkar

Since Specialization

Citations

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

Fields of papers citing papers by Varada Kolhatkar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Varada Kolhatkar

This figure shows the co-authorship network connecting the top 25 collaborators of Varada Kolhatkar. A scholar is included among the top collaborators of Varada Kolhatkar 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 Varada Kolhatkar. Varada Kolhatkar 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:

13 of 13 papers shown

1.

Kolhatkar, Varada, Nithum Thain, Jeffrey Sorensen, Lucas Dixon, & Maite Taboada. (2023). Classifying constructive comments. First Monday. 2 indexed citations

2.

Kolhatkar, Varada, et al.. (2019). The SFU Opinion and Comments Corpus: A Corpus for the Analysis of Online News Comments. PubMed. 4(2). 155–190. 49 indexed citations

3.

Kolhatkar, Varada, et al.. (2018). Anaphora With Non-nominal Antecedents in Computational Linguistics: a Survey. Computational Linguistics. 44(3). 547–612. 15 indexed citations

4.

Poesio, Massimo, Varada Kolhatkar, Nafise Sadat Moosavi, et al.. (2018). Anaphora Resolution with the ARRAU Corpus. 11–22. 21 indexed citations

5.

Kolhatkar, Varada & Maite Taboada. (2017). Constructive Language in News Comments. 11–17. 24 indexed citations

6.

Kolhatkar, Varada & Maite Taboada. (2017). Using New York Times Picks to Identify Constructive Comments. 100–105. 12 indexed citations

7.

Arbuckle, Luk, et al.. (2016). A unified framework for evaluating the risk of re-identification of text de-identification tools. Journal of Biomedical Informatics. 63. 174–183. 16 indexed citations

8.

Kolhatkar, Varada & Graeme Hirst. (2014). Resolving Shell Nouns. 499–510. 10 indexed citations

9.

Kolhatkar, Varada, Heike Zinsmeister, & Graeme Hirst. (2013). Interpreting Anaphoric Shell Nouns using Antecedents of Cataphoric Shell Nouns as Training Data. 300–310. 14 indexed citations

10.

Kolhatkar, Varada, Heike Zinsmeister, & Graeme Hirst. (2013). Annotating Anaphoric Shell Nouns with their Antecedents. 112–121. 8 indexed citations

11.

Kolhatkar, Varada & Graeme Hirst. (2012). Resolving this-issue anaphora. Empirical Methods in Natural Language Processing. 1255–1265. 9 indexed citations

12.

Pedersen, Ted & Varada Kolhatkar. (2009). WordNet::SenseRelate::AllWords. 17–20. 40 indexed citations

13.

Stemmer, Georg, Varada Kolhatkar, Andrew S. Cassidy, et al.. (2009). Analyzing features for automatic age estimation on cross-sectional data. 2923–2926. 19 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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