Diane Napolitano

948 total citations
12 papers, 234 citations indexed

About

Diane Napolitano is a scholar working on Artificial Intelligence, Developmental and Educational Psychology and Information Systems. According to data from OpenAlex, Diane Napolitano has authored 12 papers receiving a total of 234 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 3 papers in Developmental and Educational Psychology and 1 paper in Information Systems. Recurrent topics in Diane Napolitano's work include Text Readability and Simplification (10 papers), Natural Language Processing Techniques (9 papers) and Topic Modeling (7 papers). Diane Napolitano is often cited by papers focused on Text Readability and Simplification (10 papers), Natural Language Processing Techniques (9 papers) and Topic Modeling (7 papers). Diane Napolitano collaborates with scholars based in United States and Australia. Diane Napolitano's co-authors include Kathleen M. Sheehan, Michael Flor, Joel Tetreault, Aoife Cahill, Irene Kostin, Nitin Madnani, Shervin Malmasi, Keelan Evanini, Yao Qian and Robert Pugh and has published in prestigious journals such as The Elementary School Journal, Journal of Educational Computing Research and CALICO Journal.

In The Last Decade

Diane Napolitano

12 papers receiving 213 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Diane Napolitano United States 8 204 66 22 21 18 12 234
Jianmin Dai United States 5 125 0.6× 70 1.1× 57 2.6× 42 2.0× 10 0.6× 13 191
Andrew Finch South Korea 8 150 0.7× 17 0.3× 41 1.9× 10 0.5× 48 2.7× 26 237
Tongguang Li Australia 7 96 0.5× 59 0.9× 53 2.4× 26 1.2× 7 0.4× 14 207
Ramon Ziai Germany 11 297 1.5× 91 1.4× 49 2.2× 70 3.3× 30 1.7× 26 352
Elena Volodina Sweden 11 295 1.4× 87 1.3× 7 0.3× 24 1.1× 42 2.3× 67 339
Jacob Steiss United States 5 74 0.4× 42 0.6× 65 3.0× 15 0.7× 21 1.2× 8 185
Sane Yagi United Arab Emirates 8 136 0.7× 10 0.2× 9 0.4× 16 0.8× 49 2.7× 35 215
John Maurice Gayed Japan 4 112 0.5× 44 0.7× 52 2.4× 29 1.4× 25 1.4× 8 256
Sarah Schwarm United States 4 227 1.1× 35 0.5× 13 0.6× 18 0.9× 6 0.3× 6 249
Youngsun Moon South Korea 6 85 0.4× 67 1.0× 85 3.9× 25 1.2× 30 1.7× 11 228

Countries citing papers authored by Diane Napolitano

Since Specialization
Citations

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

Fields of papers citing papers by Diane Napolitano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Diane Napolitano

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

All Works

12 of 12 papers shown
1.
Sheehan, Kathleen M. & Diane Napolitano. (2019). Generating Reliable Feedback About Students’ Performances Within an Automated Reading Tutor. Journal of Educational Computing Research. 58(2). 459–477. 1 indexed citations
2.
Madnani, Nitin, et al.. (2018). Writing Mentor: Self-Regulated Writing Feedback for Struggling Writers. International Conference on Computational Linguistics. 113–117. 8 indexed citations
3.
Burstein, Jill, et al.. (2018). Writing MentorTM: Writing Progress Using Self-Regulated Writing Support. 2(1). 285–313. 8 indexed citations
4.
Madnani, Nitin, Aoife Cahill, Daniel Blanchard, et al.. (2018). A Robust Microservice Architecture for Scaling Automated Scoring Applications. ETS Research Report Series. 2018(1). 1–8. 5 indexed citations
5.
Malmasi, Shervin, Keelan Evanini, Aoife Cahill, et al.. (2017). A Report on the 2017 Native Language Identification Shared Task. 64 indexed citations
6.
Yoon, Su‐Youn, Yeonsuk Cho, & Diane Napolitano. (2016). Spoken Text Difficulty Estimation Using Linguistic Features. 267–276. 7 indexed citations
7.
Napolitano, Diane, et al.. (2015). Online Readability and Text Complexity Analysis with TextEvaluator. 16 indexed citations
8.
Sheehan, Kathleen M., Michael Flor, Diane Napolitano, & Chaitanya Ramineni. (2015). Using TextEvaluator® to Quantify Sources of Linguistic Complexity in Textbooks Targeted at First‐Grade Readers Over the Past Half Century. ETS Research Report Series. 2015(2). 1–17. 8 indexed citations
9.
Sheehan, Kathleen M., Irene Kostin, Diane Napolitano, & Michael Flor. (2014). The TextEvaluator Tool. The Elementary School Journal. 115(2). 184–209. 58 indexed citations
10.
Cahill, Aoife, Nitin Madnani, Joel Tetreault, & Diane Napolitano. (2013). Robust Systems for Preposition Error Correction Using Wikipedia Revisions. North American Chapter of the Association for Computational Linguistics. 507–517. 28 indexed citations
11.
Sheehan, Kathleen M., Michael Flor, & Diane Napolitano. (2013). A Two-Stage Approach for Generating Unbiased Estimates of Text Complexity. 49–58. 24 indexed citations
12.
Napolitano, Diane & Amanda Stent. (2009). TechWriter. CALICO Journal. 26(3). 611–625. 7 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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2026