Building the Bridge

Topic Modeling for Comparative Research

Datos Bibliográficos

ID12971167
AutoresFabienne Lind (0000-0002-4978-9415, University of Vienna, autor de correspondencia), Jakob-Moritz Eberl (0000-0002-5613-760X, University of Vienna), Olga Eisele (0000-0002-6604-3498, University of Vienna), Tobias Heidenreich (0000-0001-9070-0550, University of Vienna), Sebastian Galyga (0000-0003-2642-0815, University of Vienna), Hajo Boomgaarden (0000-0002-5260-1284, University of Vienna)
Año2021
Volumen16
Número2
Páginas96-114
Fecha de publicación2021-09-07
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaCommunication Methods and Measures (JOURNAL)
Identificadores de la revistaISSN: 1931-2458 • E-ISSN: 1931-2466
EditorialTaylor & Francis (PUBLISHER • GB)
DOI10.1080/19312458.2021.1965973
OpenAlexW3198615978
IdiomaEN
Citas recibidas17
Referencias citadas33

In communication research, topic modeling is primarily used for discovering systematic patterns in monolingual text corpora. To advance the usage, we provide an overview of recently presented strategies to extract topics from multilingual text collections for the purpose of comparative research. Moreover, we discuss, demonstrate, and facilitate the usability of the “Polylingual Topic Model” (PLTM) for such analyses. The appeal of this model is that it derives lists of related clustered words in different languages with little reliance on translation or multilingual dictionaries and without the need for manual post-hoc matching of topics. PLTM bridges the gap between languages by making use of document connections in training documents. As these training documents are the crucial resource for the model, we compare model evaluation metrics for different strategies to build training documents. By discussing the advantages and limitations of the different strategies in respect to different scenarios, our study contributes to the methodological discussion on automated content analysis of multilingual text corpora

Bridge (graph theory · Data science · Human–computer interaction · Information retrieval · Matching (statistics · Natural language processing · Resource (disambiguation · Topic model · Usability · World Wide Web · Advanced Text Analysis Techniques · Computational and Text Analysis Methods · Computer Science · Topic Modeling · Artificial Intelligence