Sina Zarrieß

30 papers and 115 indexed citations i.

About

Sina Zarrieß is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Social Psychology. According to data from OpenAlex, Sina Zarrieß has authored 30 papers receiving a total of 115 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Artificial Intelligence, 14 papers in Computer Vision and Pattern Recognition and 2 papers in Social Psychology. Recurrent topics in Sina Zarrieß’s work include Natural Language Processing Techniques (16 papers), Topic Modeling (15 papers) and Multimodal Machine Learning Applications (12 papers). Sina Zarrieß is often cited by papers focused on Natural Language Processing Techniques (16 papers), Topic Modeling (15 papers) and Multimodal Machine Learning Applications (12 papers). Sina Zarrieß collaborates with scholars based in Germany, United States and Spain. Sina Zarrieß's co-authors include David Schlangen, Casey Kennington, Jonas Kuhn, Julian Hough, Carina Silberer, Gemma Boleda, Raquel Fernández, David DeVault, Bernd Bohnet and Monique Meuschke and has published in prestigious journals such as Language Resources and Evaluation, Information and Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).

In The Last Decade

Co-authorship network of co-authors of Sina Zarrieß i

Fields of papers citing papers by Sina Zarrieß

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Sina Zarrieß

Since Specialization
Citations

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

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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