Çağrı Çöltekin

1.9k total citations · 1 hit paper
48 papers, 745 citations indexed

About

Çağrı Çöltekin is a scholar working on Artificial Intelligence, Developmental and Educational Psychology and Linguistics and Language. According to data from OpenAlex, Çağrı Çöltekin has authored 48 papers receiving a total of 745 indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Artificial Intelligence, 6 papers in Developmental and Educational Psychology and 5 papers in Linguistics and Language. Recurrent topics in Çağrı Çöltekin's work include Natural Language Processing Techniques (33 papers), Topic Modeling (19 papers) and Authorship Attribution and Profiling (10 papers). Çağrı Çöltekin is often cited by papers focused on Natural Language Processing Techniques (33 papers), Topic Modeling (19 papers) and Authorship Attribution and Profiling (10 papers). Çağrı Çöltekin collaborates with scholars based in Germany, Netherlands and China. Çağrı Çöltekin's co-authors include Taraka Rama, Marcos Zampieri, Leon Derczynski, Pepa Atanasova, Sara Rosenthal, Georgi Karadzhov, Hamdy Mubarak, Preslav Nakov, John Nerbonne and Özlem Çetinoğlu and has published in prestigious journals such as Cognitive Science, Language Resources and Evaluation and Lingua.

In The Last Decade

Çağrı Çöltekin

45 papers receiving 640 citations

Hit Papers

align trajectories

What are hit papers?

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.

SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020)

2020 244 citations Marcos Zampieri, Preslav Nakov et al. Research at the University of Copenhagen (University of Copenhagen) profile →

Peers

Çağrı Çöltekin

AI

SP

COMMU

IS

ECP

Carol Van Ess-Dykema United States

Klaus Ries United States

Chee Wee Leong United States

Bente Mægaard Denmark

Samira Shaikh United States

Karine Megerdoomian United States

Jan Odijk Netherlands

Scott Nowson United Kingdom

Volha Petukhova Netherlands

Alex Chengyu Fang Hong Kong

Carol Van Ess-Dykema United States

Çağrı Çöltekin

969 ×1.5

AI

60 ×0.6

SP

15 ×0.2

COMMU

57 ×1.0

IS

129 ×2.5

ECP

Citations per year, relative to Çağrı Çöltekin Çağrı Çöltekin (= 1×) peers Carol Van Ess-Dykema

Countries citing papers authored by Çağrı Çöltekin

Since Specialization

Citations

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

Fields of papers citing papers by Çağrı Çöltekin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Çağrı Çöltekin

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

All Works

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20 of 20 papers shown

1.

Çöltekin, Çağrı, Rob van der Goot, Tommi Jauhiainen, et al.. (2023). Findings of the VarDial Evaluation Campaign 2023. IT University Of Copenhagen (IT University of Copenhagen). 251–261. 17 indexed citations

2.

Çöltekin, Çağrı, A. Seza Doğruöz, & Özlem Çetinoğlu. (2022). Resources for Turkish natural language processing: A critical survey. Language Resources and Evaluation. 57(1). 449–488. 6 indexed citations

3.

Çöltekin, Çağrı, A. Seza Doğruöz, & Özlem Çetinoğlu. (2022). Correction to: Resources for Turkish natural language processing: A critical survey. Language Resources and Evaluation. 57(1). 489–489. 1 indexed citations

4.

Çöltekin, Çağrı & Taraka Rama. (2022). What do complexity measures measure? Correlating and validating corpus-based measures of morphological complexity. Linguistics Vanguard. 9(s1). 27–43. 4 indexed citations

5.

Erjavec, Tomaž, Maciej Ogrodniczuk, Petya Osenova, et al.. (2021). ParlaMint: Comparable Corpora of European Parliamentary Data. SZTE Publicatio Repozitórium (University of Szeged). 1 indexed citations

6.

Çöltekin, Çağrı, et al.. (2021). ROFF - A Romanian Twitter Dataset for Offensive Language. 895–900. 4 indexed citations

7.

Çöltekin, Çağrı. (2020). Dialect Identification under Domain Shift: Experiments with Discriminating Romanian and Moldavian. International Conference on Computational Linguistics. 186–192. 6 indexed citations

8.

Çöltekin, Çağrı. (2020). A Corpus of Turkish Offensive Language on Social Media. Language Resources and Evaluation. 6174–6184. 74 indexed citations

9.

Çöltekin, Çağrı, et al.. (2020). Reproduction and Replication: A Case Study with Automatic Essay Scoring.. Language Resources and Evaluation. 5603–5613. 5 indexed citations

10.

Zampieri, Marcos, Preslav Nakov, Sara Rosenthal, et al.. (2020). SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020). Research at the University of Copenhagen (University of Copenhagen). 1425–1447. 244 indexed citations breakdown →

11.

Çöltekin, Çağrı, et al.. (2018). Tübingen-Oslo Team at the VarDial 2018 Evaluation Campaign: An Analysis of N-gram Features in Language Variety Identification. International Conference on Computational Linguistics. 55–65. 11 indexed citations

12.

Çöltekin, Çağrı, Bill Thompson, Vera Demberg, et al.. (2018). Using Universal Dependencies in cross-linguistic complexity research. SPIRE - Sciences Po Institutional REpository. 8–17. 13 indexed citations

13.

Çöltekin, Çağrı & Taraka Rama. (2018). Tübingen-Oslo at SemEval-2018 Task 2: SVMs perform better than RNNs in Emoji Prediction. 34–38. 29 indexed citations

14.

Boll‐Avetisyan, Natalie, et al.. (2018). Short-term exposure enhances perception of both between- and within-category acoustic information. UvA-DARE (University of Amsterdam). 114–118. 5 indexed citations

15.

Çöltekin, Çağrı, et al.. (2018). Identifying Depression on Reddit: The Effect of Training Data. 9–12. 72 indexed citations

16.

Rama, Taraka & Çağrı Çöltekin. (2016). LSTM Autoencoders for Dialect Analysis. International Conference on Computational Linguistics. 25–32. 7 indexed citations

17.

Çöltekin, Çağrı & Taraka Rama. (2016). Discriminating Similar Languages with Linear SVMs and Neural Networks.. International Conference on Computational Linguistics. 15–24. 22 indexed citations

18.

Çöltekin, Çağrı, et al.. (2015). Using Gabmap. Lingua. 178. 71–83. 14 indexed citations

19.

Çöltekin, Çağrı, et al.. (2013). A linear model for exploring types of vowel harmony. 3. 174–192. 3 indexed citations

20.

Ma, Jianhua, et al.. (2009). Proceedings of The 14th Student Session of the European Summer School for Logic, Language, and Information. 3 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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