The Challenges of Multi-dimensional Sentiment Analysis Across Languages

Emily Öhman, Timo Honkela, Jörg Tiedemann


Abstract
This paper outlines a pilot study on multi-dimensional and multilingual sentiment analysis of social media content. We use parallel corpora of movie subtitles as a proxy for colloquial language in social media channels and a multilingual emotion lexicon for fine-grained sentiment analyses. Parallel data sets make it possible to study the preservation of sentiments and emotions in translation and our assessment reveals that the lexical approach shows great inter-language agreement. However, our manual evaluation also suggests that the use of purely lexical methods is limited and further studies are necessary to pinpoint the cross-lingual differences and to develop better sentiment classifiers.
Anthology ID:
W16-4315
Volume:
Proceedings of the Workshop on Computational Modeling of People’s Opinions, Personality, and Emotions in Social Media (PEOPLES)
Month:
December
Year:
2016
Address:
Osaka, Japan
Venues:
PEOPLES | WS
SIG:
Publisher:
The COLING 2016 Organizing Committee
Note:
Pages:
138–142
Language:
URL:
https://www.aclweb.org/anthology/W16-4315
DOI:
Bib Export formats:
BibTeX MODS XML EndNote
PDF:
http://aclanthology.lst.uni-saarland.de/W16-4315.pdf