Susanne Wolff
- Artificial Intelligence top 5%
- Information Systems top 10%
- Education top 10%
- Developmental and Educational Psychology top 10%
- Literature and Literary Theory top 10%
- Co-authors
- Jill BursteinChi LuMartin ChodorowKaren KukichThomas QuinlanDerrick HigginsJohn B. ThomasThomas R. Williams
- Topics
- Natural Language Processing Techniques (7 papers)Topic Modeling (4 papers)Lexicography and Language Studies (3 papers)
- Cited by
- Artificial IntelligenceDevelopmental and Educational PsychologyComputer Science Applications
- Journals
- IEEE Transactions on Information TheoryMethods of Information in MedicineETS Research Report Series
- Partner nations
- United States
In The Last Decade
Susanne Wolff
13 papers receiving 321 citations
Peers
Comparison fields: 5 of 59
- Artificial Intelligence 239
- Information Systems 106
- Education 68
- Developmental and Educational Psychology 65
- Literature and Literary Theory 29
Countries citing papers authored by Susanne Wolff
This map shows the geographic impact of Susanne Wolff'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 Susanne Wolff with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Susanne Wolff more than expected).
Fields of papers citing papers by Susanne Wolff
This network shows the impact of papers produced by Susanne Wolff. 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 Susanne Wolff. The network helps show where Susanne Wolff may publish in the future.
Co-authorship network of co-authors of Susanne Wolff
This figure shows the co-authorship network connecting the top 25 collaborators of Susanne Wolff. A scholar is included among the top collaborators of Susanne Wolff 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 Susanne Wolff. Susanne Wolff is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Detecting Missing Hyphens in Learner Text | 4 |
| 2 | Evaluating the Construct-Coverage of the e-rater[R] Scoring Engine. Research Report. ETS RR-09-01. | 21 |
| 3 | 41 | |
| 4 | 52 | |
| 5 | 107 | |
| 6 | 15 | |
| 7 | Enriching Automated Essay Scoring Using Discourse Marking. | 52 |
| 8 | 2 | |
| 9 | 2 | |
| 10 | 7 | |
| 11 | Lexical entries and word formation | 3 |
| 12 | 18 | |
| 13 | 48 |
About Susanne Wolff
Susanne Wolff is a scholar working on Artificial Intelligence, Language and Linguistics and Literature and Literary Theory, having authored 13 papers that have together received 372 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (7 papers), Topic Modeling (4 papers) and Lexicography and Language Studies (3 papers). The work is most often cited by research in Artificial Intelligence (239 citations), Developmental and Educational Psychology (65 citations) and Computer Science Applications (27 citations). Susanne Wolff has collaborated with scholars based in United States. Frequent co-authors include Jill Burstein, Chi Lu, Martin Chodorow, Karen Kukich, Thomas Quinlan, Derrick Higgins, John B. Thomas, Thomas R. Williams, Bruce Kaplan and James J. Nolan. Their work appears in journals such as IEEE Transactions on Information Theory, Methods of Information in Medicine and ETS Research Report Series.
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.