@inproceedings{ohman-etal-2016-challenges,
    title = "The Challenges of Multi-dimensional Sentiment Analysis Across Languages",
    author = {{\"O}hman, Emily  and
      Honkela, Timo  and
      Tiedemann, J{\"o}rg},
    editor = "Nissim, Malvina  and
      Patti, Viviana  and
      Plank, Barbara",
    booktitle = "Proceedings of the Workshop on Computational Modeling of People`s Opinions, Personality, and Emotions in Social Media ({PEOPLES})",
    month = dec,
    year = "2016",
    address = "Osaka, Japan",
    publisher = "The COLING 2016 Organizing Committee",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/W16-4315/",
    pages = "138--142",
    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."
}