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.
The Stanford CoreNLP Natural Language Processing Toolkit
Countries citing papers authored by Steven Bethard
Since
Specialization
Citations
This map shows the geographic impact of Steven Bethard'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 Steven Bethard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steven Bethard more than expected).
This network shows the impact of papers produced by Steven Bethard. 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 Steven Bethard. The network helps show where Steven Bethard may publish in the future.
Co-authorship network of co-authors of Steven Bethard
This figure shows the co-authorship network connecting the top 25 collaborators of Steven Bethard.
A scholar is included among the top collaborators of Steven Bethard 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 Steven Bethard. Steven Bethard is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Bethard, Steven & Jonathan Parker. (2016). A Semantically Compositional Annotation Scheme for Time Normalization. Language Resources and Evaluation. 3779–3786.16 indexed citations
10.
Bethard, Steven, et al.. (2016). Facing the most difficult case of semantic role labeling: A collaboration of word embeddings and co-training. International Conference on Computational Linguistics. 1275–1284.3 indexed citations
Bethard, Steven, et al.. (2013). CU : Computational Assessment of Short Free Text Answers - A Tool for Evaluating Students' Understanding. Joint Conference on Lexical and Computational Semantics. 603–607.5 indexed citations
16.
Bethard, Steven, et al.. (2012). Identifying science concepts and student misconceptions in an interactive essay writing tutor. North American Chapter of the Association for Computational Linguistics. 12–21.7 indexed citations
17.
Munro, Robert, Steven Bethard, Victor Kuperman, et al.. (2010). Crowdsourcing and language studies: the new generation of linguistic data. Max Planck Digital Library. 122–130.94 indexed citations
18.
Bethard, Steven, et al.. (2008). Building a Corpus of Temporal-Causal Structure.. Language Resources and Evaluation.33 indexed citations
19.
Bethard, Steven, et al.. (2004). Automatic Extraction of Opinion Propositions and their Holders. National Conference on Artificial Intelligence.111 indexed citations
20.
Pradhan, Sameer, Steven Bethard, Wayne Ward, et al.. (2002). Building a Foundation System for Producing Short Answers to Factual Questions.. Text REtrieval Conference.6 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.