@inproceedings{kruspe-etal-2020-cross,
    title = "Cross-language sentiment analysis of {European} {Twitter} messages during the {COVID-19} pandemic",
    author = {Kruspe, Anna  and
      H{\"a}berle, Matthias  and
      Kuhn, Iona  and
      Zhu, Xiao Xiang},
    editor = "Verspoor, Karin  and
      Cohen, Kevin Bretonnel  and
      Dredze, Mark  and
      Ferrara, Emilio  and
      May, Jonathan  and
      Munro, Robert  and
      Paris, Cecile  and
      Wallace, Byron",
    booktitle = "Proceedings of the 1st Workshop on {NLP} for {COVID-19} at {ACL} 2020",
    month = jul,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2020.nlpcovid19-acl.14/",
    abstract = "In this paper, we analyze Twitter messages (tweets) collected during the first months of the COVID-19 pandemic in Europe with regard to their sentiment. This is implemented with a neural network for sentiment analysis using multilingual sentence embeddings. We separate the results by country of origin, and correlate their temporal development with events in those countries. This allows us to study the effect of the situation on people{'}s moods. We see, for example, that lockdown announcements correlate with a deterioration of mood in almost all surveyed countries, which recovers within a short time span."
}