Paul Heymann

About

Paul Heymann is a scholar working on Information Systems, Artificial Intelligence and Sociology and Political Science. According to data from OpenAlex, Paul Heymann has authored 3 papers receiving a total of 294 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Information Systems, 2 papers in Artificial Intelligence and 1 paper in Sociology and Political Science. Recurrent topics in Paul Heymann’s work include Spam and Phishing Detection (3 papers), Topic Modeling (1 paper) and Recommender Systems and Techniques (1 paper). Paul Heymann is often cited by papers focused on Spam and Phishing Detection (3 papers), Topic Modeling (1 paper) and Recommender Systems and Techniques (1 paper). Paul Heymann collaborates with scholars based in United States. Paul Heymann's co-authors include Georgia Koutrika and Héctor García-Molina and has published in prestigious journals such as IEEE Internet Computing, ACM Transactions on the Web and CiteSeer X (The Pennsylvania State University).

In The Last Decade

Co-authorship network of co-authors of Paul Heymann i

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Fields of papers citing papers by Paul Heymann

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Paul Heymann

Since Specialization

Citations

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