Rethinking LDA: Why Priors Matter
Impact in
Classified as
- Journal
- ScholarWorks@UMassAmherst (University of Massachusetts Amherst)
In The Last Decade
doi.org/w8313330 →Countries where authors are citing Rethinking LDA: Why Priors Matter
This map shows the geographic impact of Rethinking LDA: Why Priors Matter. 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 Rethinking LDA: Why Priors Matter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rethinking LDA: Why Priors Matter more than expected).
Fields of papers citing Rethinking LDA: Why Priors Matter
This network shows the impact of Rethinking LDA: Why Priors Matter. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Rethinking LDA: Why Priors Matter.
About Rethinking LDA: Why Priors Matter
This paper, published in 2009, received 380 indexed citations . Written by Hanna Wallach, David Mimno and Andrew McCallum covering the research area of Artificial Intelligence. It is primarily cited by scholars working on Artificial Intelligence (265 citations), Information Systems (85 citations), General Social Sciences (67 citations), Statistical and Nonlinear Physics (39 citations) and Sociology and Political Science (36 citations). Published in ScholarWorks@UMassAmherst (University of Massachusetts Amherst).
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/w8313330.