Machine translation vs. multilingual dictionaries: Assessing two strategies for the topic modeling of multilingual text collections.

Author(s)
Annie Waldherr, Daniel Maier, Christian Baden, Daniela Stoltenberg, Maya De Vries-Kedem
Abstract

The goal of this paper is to evaluate two methods for the topic modeling of multilingual document collections: (1) machine translation (MT), and (2) the coding of semantic concepts using a multilingual dictionary (MD) prior to topic modeling. We empirically assess the consequences of these approaches based on both a quantitative comparison of models and a qualitative validation of each method’s potentials and weaknesses. Our case study uses two text collections (of tweets and news articles) in three languages (English, Hebrew, Arabic), covering the ongoing local conflicts between Israeli authorities, settlers, and Palestinian Bedouins in the West Bank. We find that both methods produce a large share of equivalent topics, especially in the context of fairly homogenous news discourse, yet show limited but systematic differences when applied to highly heterogenous social media discourse. While the MD model delivers a more nuanced picture of conflict-related topics, it misses several more peripheral topics, especially those unrelated to the dictionary’s focus, which are picked up by the MT model. Our study is a first step toward instrument validation, indicating that both methods yield valid, comparable results, while method-specific differences remain.

Organisation(s)
Department of Communication
External organisation(s)
Freie Universität Berlin (FU), Hebrew University Jerusalem
Journal
Communication Methods & Measures
Volume
16
Pages
19-38
No. of pages
20
ISSN
1931-2458
DOI
https://doi.org/10.1080/19312458.2021.1955845
Publication date
2021
Peer reviewed
Yes
Austrian Fields of Science 2012
508007 Communication science, 508014 Journalism
ASJC Scopus subject areas
Communication
Portal url
https://ucrisportal.univie.ac.at/en/publications/machine-translation-vs-multilingual-dictionaries-assessing-two-strategies-for-the-topic-modeling-of-multilingual-text-collections(d0d079a2-4bdb-49ff-a954-2c90f2d12743).html