Machine Translation Weekly 55: Social Polarization Seen through Word Embeddings
This week, I am going to have a closer look at a paper that creatively uses
methods for bilingual word embeddings for social media analysis. The paper’s
preprint was uploaded last week on arXiv. The title is “We Don’t Speak the
Same Language: Interpreting Polarization through Machine
Translation,” and most of the authors CMU in
Pittsburgh.
The paper’s central assumption is that the polarization of different opinion
groups, especially in the USA, went so far that some words have totally
different meanings for those groups. For instance, saying that black lives
matter has totally different connotations for supporters of the republicans and
supporters of the democrats. The goal of the paper is to identify such concepts
that have a different meaning for the groups.
The title of the paper