@inproceedings{summa-etal-2016-microblog,
    title = "Microblog Emotion Classification by Computing Similarity in Text, Time, and Space",
    author = "Summa, Anja  and
      Resch, Bernd  and
      Strube, Michael",
    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/W16-4317/",
    pages = "153--162",
    abstract = "Most work in NLP analysing microblogs focuses on textual content thus neglecting temporal and spatial information. We present a new interdisciplinary method for emotion classification that combines linguistic, temporal, and spatial information into a single metric. We create a graph of labeled and unlabeled tweets that encodes the relations between neighboring tweets with respect to their emotion labels. Graph-based semi-supervised learning labels all tweets with an emotion."
}