Elijah Mayfield

1.1k total citations
27 papers, 599 citations indexed

About

Elijah Mayfield is a scholar working on Artificial Intelligence, Information Systems and Communication. According to data from OpenAlex, Elijah Mayfield has authored 27 papers receiving a total of 599 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 6 papers in Information Systems and 4 papers in Communication. Recurrent topics in Elijah Mayfield's work include Topic Modeling (13 papers), Natural Language Processing Techniques (8 papers) and Speech and dialogue systems (5 papers). Elijah Mayfield is often cited by papers focused on Topic Modeling (13 papers), Natural Language Processing Techniques (8 papers) and Speech and dialogue systems (5 papers). Elijah Mayfield collaborates with scholars based in United States, Switzerland and Germany. Elijah Mayfield's co-authors include Carolyn Penstein Rosé, Alan W. Black, Ross H. Nehm, Minsu Ha, G. David Adamson, Tenbroeck Smith, Diyi Yang, Dan Jurafsky, Robert E. Kraut and Karsten Stegmann and has published in prestigious journals such as Journal of the American Medical Informatics Association, Journal of Educational Measurement and Journal of Science Education and Technology.

In The Last Decade

Elijah Mayfield

27 papers receiving 565 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Elijah Mayfield United States 13 345 127 121 106 79 27 599
Kaori Nakao Japan 8 222 0.6× 105 0.8× 163 1.3× 129 1.2× 68 0.9× 14 533
Carmel Kent Israel 9 137 0.4× 173 1.4× 308 2.5× 288 2.7× 128 1.6× 25 763
Sebastian Hobert Germany 10 320 0.9× 55 0.4× 48 0.4× 109 1.0× 52 0.7× 35 483
Donggil Song United States 15 140 0.4× 235 1.9× 338 2.8× 257 2.4× 158 2.0× 35 723
Weijiao Huang Hong Kong 7 446 1.3× 120 0.9× 188 1.6× 284 2.7× 109 1.4× 12 727
Jean‐Luc Gurtner Switzerland 13 123 0.4× 200 1.6× 255 2.1× 82 0.8× 55 0.7× 27 544
Arlene W. Weiner United States 10 129 0.4× 243 1.9× 132 1.1× 59 0.6× 38 0.5× 11 406
Kai Guo Hong Kong 14 382 1.1× 210 1.7× 163 1.3× 316 3.0× 103 1.3× 40 854
Linda Galligan Australia 12 144 0.4× 46 0.4× 280 2.3× 121 1.1× 76 1.0× 66 619
Austin Pack United States 12 279 0.8× 145 1.1× 126 1.0× 218 2.1× 114 1.4× 21 761

Countries citing papers authored by Elijah Mayfield

Since Specialization
Citations

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

Fields of papers citing papers by Elijah Mayfield

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Elijah Mayfield

This figure shows the co-authorship network connecting the top 25 collaborators of Elijah Mayfield. A scholar is included among the top collaborators of Elijah Mayfield 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 Elijah Mayfield. Elijah Mayfield 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.
Jo, Yohan, Elijah Mayfield, Chris Reed, & Eduard Hovy. (2020). Machine-Aided Annotation for Fine-Grained Proposition Types in Argumentation. Language Resources and Evaluation. 1008–1018. 4 indexed citations
2.
Mayfield, Elijah, et al.. (2020). Why Attention is Not Explanation: Surgical Intervention and Causal Reasoning about Neural Models.. Language Resources and Evaluation. 1780–1790. 12 indexed citations
3.
Mayfield, Elijah & Alan W. Black. (2020). Should You Fine-Tune BERT for Automated Essay Scoring?. 151–162. 74 indexed citations
4.
Mayfield, Elijah, et al.. (2019). Equity Beyond Bias in Language Technologies for Education. 444–460. 21 indexed citations
5.
Mayfield, Elijah & Alan W. Black. (2019). Stance Classification, Outcome Prediction, and Impact Assessment:. 65–77. 3 indexed citations
6.
Mayfield, Elijah, et al.. (2018). Trustworthy Automated Essay Scoring without Explicit Construct Validity.. National Conference on Artificial Intelligence. 9 indexed citations
7.
Howley, Iris, Elijah Mayfield, & Carolyn Penstein Rosé. (2018). Missing Something? Authority in Collaborative Learning. Research Showcase @ Carnegie Mellon University (Carnegie Mellon University). 1. 336. 2 indexed citations
8.
Pan, Shimei, Elijah Mayfield, Jie Lü, & Jennifer C. Lai. (2015). Signals of Expertise in Public and Enterprise Social Q&A. 670–673. 1 indexed citations
9.
Mayfield, Elijah, G. David Adamson, & Carolyn Penstein Rosé. (2013). Recognizing Rare Social Phenomena in Conversation: Empowerment Detection in Support Group Chatrooms. Meeting of the Association for Computational Linguistics. 104–113. 4 indexed citations
10.
Mayfield, Elijah, M. Barton Laws, Ira B. Wilson, & Carolyn Penstein Rosé. (2013). Automating annotation of information-giving for analysis of clinical conversation. Journal of the American Medical Informatics Association. 21(e1). e122–e128. 21 indexed citations
11.
Mayfield, Elijah, G. David Adamson, & Carolyn Penstein Rosé. (2012). Hierarchical Conversation Structure Prediction in Multi-Party Chat. Annual Meeting of the Special Interest Group on Discourse and Dialogue. 60–69. 22 indexed citations
12.
Wang, William Yang, Elijah Mayfield, Suresh Naidu, & Jeremiah Dittmar. (2012). Historical Analysis of Legal Opinions with a Sparse Mixed-Effects Latent Variable Model. London School of Economics and Political Science Research Online (London School of Economics and Political Science). 740–749. 17 indexed citations
13.
Mu, Jin, Karsten Stegmann, Elijah Mayfield, Carolyn Penstein Rosé, & Frank Fischer. (2012). The ACODEA framework: Developing segmentation and classification schemes for fully automatic analysis of online discussions. International Journal of Computer-Supported Collaborative Learning. 7(2). 285–305. 52 indexed citations
14.
Ogan, Amy, et al.. (2012). "Oh dear stacy!". 39–48. 36 indexed citations
15.
Mayfield, Elijah, G. David Adamson, Alexander I. Rudnicky, & Carolyn Penstein Rosé. (2012). Computational representation of discourse practices across populations in task-based dialogue. 67–76. 3 indexed citations
16.
Mayfield, Elijah & Carolyn Penstein Rosé. (2011). Recognizing Authority in Dialogue with an Integer Linear Programming Constrained Model. Meeting of the Association for Computational Linguistics. 1018–1026. 21 indexed citations
17.
Mayfield, Elijah, et al.. (2011). Data-Driven Interaction Patterns: Authority and Information Sharing in Dialogue. 4 indexed citations
18.
Mayfield, Elijah & Carolyn Penstein Rosé. (2010). An Interactive Tool for Supporting Error Analysis for Text Mining. North American Chapter of the Association for Computational Linguistics. 25–28. 28 indexed citations
19.
Mayfield, Elijah, et al.. (2010). Sentiment Classification using Automatically Extracted Subgraph Features. North American Chapter of the Association for Computational Linguistics. 131–139. 23 indexed citations
20.
Mayfield, Elijah & Carolyn Penstein Rosé. (2010). Using feature construction to avoid large feature spaces in text classification. 1299–1306. 8 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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