Stable topic modeling for web science: Granulated LDA

S. Koltcov, S.I. Nikolenko, O. Koltsova, Светлана Сергеевна Бодрунова

Research output

3 Citations (Scopus)

Abstract

Topic modeling is a powerful tool for analyzing large collections of user-generated web content, but it still suffers from problems with topic stability, which are especially important for social sciences. We evaluate stability for differenttopic models and propose a new model, granulated LDA,that samples short sequences of neighboring words at once. We show that gLDA exhibits very stable results.
Original languageUndefined
Title of host publicationWebSci 2016 - Proceedings of the 2016 ACM Web Science Conference
Pages342-343
Publication statusPublished - 2016

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