Dagmar Divjak
- Language and Linguistics top 1%
- Artificial Intelligence top 5%
- Experimental and Cognitive Psychology top 5%
- Developmental and Educational Psychology top 10%
- Cognitive Neuroscience top 10%
- Co-authors
- Stefan Τh. GriesPetar MilinAntti ArppeR. Harald BaayenEwa DąbrowskaSrdan MedimorecNatalia LevshinaSerge Sharoff
- Topics
- Natural Language Processing Techniques (16 papers)Language, Metaphor, and Cognition (15 papers)Neurobiology of Language and Bilingualism (10 papers)
- Journals
- Journal of Experimental Psychology Learning Memory and CognitionCognitive ScienceLanguage Learning
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Dagmar Divjak
43 papers receiving 560 citations
Peers
Comparison fields: 5 of 54
- Language and Linguistics 363
- Artificial Intelligence 255
- Experimental and Cognitive Psychology 237
- Developmental and Educational Psychology 147
- Cognitive Neuroscience 112
Countries citing papers authored by Dagmar Divjak
This map shows the geographic impact of Dagmar Divjak'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 Dagmar Divjak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dagmar Divjak more than expected).
Fields of papers citing papers by Dagmar Divjak
This network shows the impact of papers produced by Dagmar Divjak. 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 Dagmar Divjak. The network helps show where Dagmar Divjak may publish in the future.
Co-authorship network of co-authors of Dagmar Divjak
This figure shows the co-authorship network connecting the top 25 collaborators of Dagmar Divjak. A scholar is included among the top collaborators of Dagmar Divjak 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 Dagmar Divjak. Dagmar Divjak is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 0 | |
| 8 | 0 | |
| 9 | 3 | |
| 10 | 2 | |
| 11 | 2 | |
| 12 | 6 | |
| 13 | 4 | |
| 14 | 0 | |
| 15 | 9 | |
| 16 | 30 | |
| 17 | 0 | |
| 18 | Designing and evaluating a Russian tagset | 28 |
| 19 | On trying in Russian: a tentative network model for near(er)-synonyms | 11 |
| 20 | On the expression of purpose in Russian: augmented teleonomic versus čtoby-constructions | 1 |
About Dagmar Divjak
Dagmar Divjak is a scholar working on Language and Linguistics, Linguistics and Language and Experimental and Cognitive Psychology, having authored 54 papers that have together received 630 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (16 papers), Language, Metaphor, and Cognition (15 papers) and Neurobiology of Language and Bilingualism (10 papers). The work is most often cited by research in Language and Linguistics (363 citations), Experimental and Cognitive Psychology (237 citations) and Linguistics and Language (65 citations). Dagmar Divjak has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Stefan Τh. Gries, Petar Milin, Antti Arppe, R. Harald Baayen, Ewa Dąbrowska, Srdan Medimorec, Natalia Levshina, Serge Sharoff, Tomaž Erjavec and Anna Feldman. Their work appears in journals such as Journal of Experimental Psychology Learning Memory and Cognition, Cognitive Science and Language Learning.
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.