Guy Rosin

1.4k citations
7 papers · 87 · h-index 5

Impact in

    • Topic Modeling
    • Natural Language Processing Techniques
    • Advanced Text Analysis Techniques
    • Speech and dialogue systems
    • Sentiment Analysis and Opinion Mining
    • Data Stream Mining Techniques
    • Language and cultural evolution

Papers in

Journals
CERN Document Server (European Organization for Nuclear Research) (1 paper)arXiv (Cornell University) (1 paper)Findings of the Association for Computational Linguistics: NAACL 2022 (1 paper)
Partner nations
IsraelUnited States

In The Last Decade

Guy Rosin

7 papers receiving 78 citations

Peers

Guy Rosin
Comparison fields: 5 of 29
  • Artificial Intelligence 70
  • Cultural Studies 17
  • General Social Sciences 2
  • Signal Processing 5
  • Information Systems 10
Replace Marco Antonio Sobrevilla Cabezudo with:
Marco Antonio Sobrevilla Cabezudo Brazil
Andrea Santilli Italy
Ninareh Mehrabi United States
Barun Patra United States
Delphine Bernhard France
Fereshte Khani United States
Marius Mosbach Germany
Marie Candito France
Andrew Drozdov United States
Damien Sileo France
Guy Rosin relative to Marco Antonio Sobrevilla Cabezudo Brazil Marco Antonio Sobrevilla Cabezudo's profile →
Citations per field
00.5×3.4×
Marco Antonio Sobrevilla Cabezudo · 1×
Citations per year

Countries citing papers authored by Guy Rosin

Since Specialization
Citations

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

Fields of papers citing papers by Guy Rosin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 7 scholars most cited alongside Guy Rosin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Guy Rosin Line = papers co-authored together Guy Rosin links everyone, so they are left out of the graph.

All Works

7 of 7 papers shown

About Guy Rosin

Guy Rosin is a scholar working on Artificial Intelligence, Cultural Studies, Electrical and Electronic Engineering, Nuclear and High Energy Physics and Sociology and Political Science, having authored 7 papers that have together received 87 indexed citations. Recurring topics across this work include Advanced Text Analysis Techniques (4 papers), Language and cultural evolution (3 papers), Topic Modeling (3 papers), Particle Detector Development and Performance (2 papers), Radiation Effects in Electronics (2 papers), Web Data Mining and Analysis (1 paper), Silicon and Solar Cell Technologies (1 paper) and Time Series Analysis and Forecasting (1 paper). The work is most often cited by research in Artificial Intelligence (70 citations), Cultural Studies (17 citations), General Social Sciences (2 citations), Signal Processing (5 citations) and Information Systems (10 citations). Guy Rosin has collaborated with scholars based in Israel and United States. Frequent co-authors include Kira Radinsky, Ido Guy, Uriel Singer, J. Kierstead, S. A. Stucci, P. Kuczewski and R.R. Burns. Their work appears in journals such as CERN Document Server (European Organization for Nuclear Research), arXiv (Cornell University) and Findings of the Association for Computational Linguistics: NAACL 2022.

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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