Like It or Not

338 indexed citations

Abstract

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About

This paper, published in 2016, received 338 indexed citations. Written by Anastasia Giachanou and Fábio Crestani covering the research area of Artificial Intelligence. It is primarily cited by scholars working on Artificial Intelligence (258 citations), Sociology and Political Science (98 citations) and Information Systems (81 citations). Published in ACM Computing Surveys.

In The Last Decade

doi.org/10.1145/2938640 →

Countries where authors are citing Like It or Not

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Citations

This map shows the geographic impact of Like It or Not. 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 Like It or Not with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Like It or Not more than expected).

Fields of papers citing Like It or Not

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Like It or Not. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Like It or Not.

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.

This paper is also available at doi.org/10.1145/2938640.

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