This map shows the geographic impact of Shane Bergsma'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 Shane Bergsma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shane Bergsma more than expected).
This network shows the impact of papers produced by Shane Bergsma. 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 Shane Bergsma. The network helps show where Shane Bergsma may publish in the future.
Co-authorship network of co-authors of Shane Bergsma
This figure shows the co-authorship network connecting the top 25 collaborators of Shane Bergsma.
A scholar is included among the top collaborators of Shane Bergsma 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 Shane Bergsma. Shane Bergsma 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.
Iqbal, Syed Muhammad Javed, et al.. (2022). CoSpot. 540–556.3 indexed citations
Bergsma, Shane & Benjamin Van Durme. (2013). Using Conceptual Class Attributes to Characterize Social Media Users. Meeting of the Association for Computational Linguistics. 710–720.27 indexed citations
6.
Post, Matt & Shane Bergsma. (2013). Explicit and Implicit Syntactic Features for Text Classification. Meeting of the Association for Computational Linguistics. 866–872.43 indexed citations
7.
Dredze, Mark, et al.. (2013). Carmen: A Twitter Geolocation System with Applications to Public Health.104 indexed citations
8.
Bergsma, Shane, Mark Dredze, Benjamin Van Durme, Theresa Wilson, & David Yarowsky. (2013). Broadly Improving User Classification via Communication-Based Name and Location Clustering on Twitter. 1010–1019.51 indexed citations
Bergsma, Shane, et al.. (2010). Predicting the Semantic Compositionality of Prefix Verbs. Empirical Methods in Natural Language Processing. 293–303.5 indexed citations
11.
Bergsma, Shane & Colin Cherry. (2010). Fast and Accurate Arc Filtering for Dependency Parsing. NPARC. 53–61.8 indexed citations
12.
Bergsma, Shane, Dekang Lin, & Dale Schuurmans. (2010). Improved Natural Language Learning via Variance-Regularization Support Vector Machines. 172–181.6 indexed citations
13.
Bergsma, Shane, Emily Pitler, & Dekang Lin. (2010). Creating Robust Supervised Classifiers via Web-Scale N-Gram Data. Meeting of the Association for Computational Linguistics. 865–874.25 indexed citations
14.
Jiampojamarn, Sittichai, et al.. (2010). Transliteration Generation and Mining with Limited Training Resources. Meeting of the Association for Computational Linguistics. 39–47.29 indexed citations
15.
Bergsma, Shane, Dekang Lin, & Randy Goebel. (2009). Web-scale N-gram models for lexical disambiguation. International Joint Conference on Artificial Intelligence. 1507–1512.61 indexed citations
Bergsma, Shane, Dekang Lin, & Randy Goebel. (2008). Distributional Identification of Non-Referential Pronouns. Meeting of the Association for Computational Linguistics. 10–18.23 indexed citations
18.
Bergsma, Shane & Grzegorz Kondrak. (2007). Alignment-Based Discriminative String Similarity. Meeting of the Association for Computational Linguistics. 656–663.40 indexed citations
19.
Bergsma, Shane, et al.. (2007). Automatic Answer Typing for How-Questions. North American Chapter of the Association for Computational Linguistics. 516–523.1 indexed citations
20.
Bergsma, Shane, et al.. (2007). Learning Noun Phrase Query Segmentation. Empirical Methods in Natural Language Processing. 819–826.78 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.