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.
This map shows the geographic impact of Jill Burstein'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 Jill Burstein with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jill Burstein more than expected).
This network shows the impact of papers produced by Jill Burstein. 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 Jill Burstein. The network helps show where Jill Burstein may publish in the future.
Co-authorship network of co-authors of Jill Burstein
This figure shows the co-authorship network connecting the top 25 collaborators of Jill Burstein.
A scholar is included among the top collaborators of Jill Burstein 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 Jill Burstein. Jill Burstein is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Burstein, Jill, et al.. (2019). Exploring Writing Analytics and Postsecondary Success Indicators.. Grantee Submission.
4.
Madnani, Nitin, et al.. (2018). Writing Mentor: Self-Regulated Writing Feedback for Struggling Writers. International Conference on Computational Linguistics. 113–117.8 indexed citations
5.
Burstein, Jill, et al.. (2017). Exploring Relationships between Writing & Broader Outcomes with Automated Writing Evaluation.. Grantee Submission.1 indexed citations
6.
Tetreault, Joel, Jill Burstein, Claudia Leacock, & Helen Yannakoudakis. (2017). Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications.1 indexed citations
Somasundaran, Swapna, Jill Burstein, & Martin Chodorow. (2014). Lexical Chaining for Measuring Discourse Coherence Quality in Test-taker Essays. International Conference on Computational Linguistics. 950–961.56 indexed citations
10.
Madnani, Nitin, Jill Burstein, John Sabatini, & Tenaha O’Reilly. (2013). Automated Scoring of Summary-Writing Tasks Designed to Measure Reading Comprehension.. Grantee Submission.
11.
Burstein, Jill, et al.. (2012). The "Language Muse"? System: Linguistically Focused Instructional Authoring. Research Report. ETS RR-12-21.. ETS Research Report Series.3 indexed citations
12.
Tetreault, Joel, Jill Burstein, & Claudia Leacock. (2011). Proceedings of the Sixth Workshop on Innovative Use of NLP for Building Educational Applications.11 indexed citations
13.
Burstein, Jill, et al.. (2010). Using Entity-Based Features to Model Coherence in Student Essays. North American Chapter of the Association for Computational Linguistics. 681–684.56 indexed citations
14.
Attali, Yigal & Jill Burstein. (2005). Automated Essay Scoring with e-rater® v.2.0. Research Report. ETS RR-04-45.. ETS Research Report Series.16 indexed citations
Higgins, Derrick, Jill Burstein, Daniel Marcu, & Claudia Gentile. (2004). Evaluating Multiple Aspects of Coherence in Student Essays. North American Chapter of the Association for Computational Linguistics. 185–192.102 indexed citations
Burstein, Jill & Daniel Marcu. (2000). Benefits of Modularity in an Automated Essay Scoring System. International Conference on Computational Linguistics. 44–50.12 indexed citations
19.
Burstein, Jill. (1999). A review of computer-based speech technology for TOEFL 2000.4 indexed citations
20.
Burstein, Jill. (1992). The stress and syntax of compound nominals. UMI eBooks.3 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.