Cem Akkaya

495 citations
11 papers · 297 indexed · h-index 7
Topics
Topic Modeling (10 papers)Sentiment Analysis and Opinion Mining (5 papers)Natural Language Processing Techniques (4 papers)
Journals
IEEE Transactions on Knowledge and Data EngineeringArtificial Intelligence in MedicineInternational Conference on Computational Linguistics

In The Last Decade

Cem Akkaya

11 papers receiving 270 citations

Peers

Cem Akkaya
Comparison fields: 5 of 42
  • Artificial Intelligence 251
  • Information Systems 39
  • Computer Science Applications 24
  • Molecular Biology 20
  • Public Health, Environmental and Occupational Health 19
Replace Georgeta Bordea with:
Georgeta Bordea Ireland
Parikshit Sondhi United States
Kalliopi Zervanou Netherlands
Ade Romadhony Indonesia
Arantza Díaz de Ilarraza Spain
Yoan Gutiérrez Spain
T. Salakoski Finland
Faiçal Azouaou Algeria
Kurt Junshean Espinosa Philippines
Suzan Üsküdarlı Türkiye
Cem Akkaya relative to Georgeta Bordea Ireland Georgeta Bordea's profile →
Citations per field
00.5×6.3×
Georgeta Bordea · 1×
Citations per year

Countries citing papers authored by Cem Akkaya

Since Specialization
Citations

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

Fields of papers citing papers by Cem Akkaya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cem Akkaya

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

All Works

11 of 11 papers shown
#WorkIndexed citations
1 2
2 68
3 1
4
First Story Detection using Entities and Relations
2
5 3
6 7
7
Improving the Impact of Subjectivity Word Sense Disambiguation on Contextual Opinion Analysis
18
8
Amazon Mechanical Turk for Subjectivity Word Sense Disambiguation
48
9 18
10 100
11 30

About Cem Akkaya

Cem Akkaya is a scholar working on Artificial Intelligence, Computer Science Applications and Information Systems, having authored 11 papers that have together received 297 indexed citations. Recurring topics across this work include Topic Modeling (10 papers), Sentiment Analysis and Opinion Mining (5 papers) and Natural Language Processing Techniques (4 papers). The work is most often cited by research in Artificial Intelligence (251 citations), Computer Science Applications (24 citations) and Health Information Management (12 citations). Cem Akkaya has collaborated with scholars based in United States, Greece and Austria. Frequent co-authors include Rada Mihalcea, Janyce Wiebe, Kostas Tsioutsiouliklis, Siddhartha Banerjee, Katharina Kaiser, Silvia Miksch, Dimitrios Gunopulos, Vana Kalogeraki and Prakhar Biyani. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Artificial Intelligence in Medicine and International Conference on Computational Linguistics.

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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