@inproceedings{abdou-etal-2018-affecthor,
    title = "{A}ffec{T}hor at {S}em{E}val-2018 Task 1: A cross-linguistic approach to sentiment intensity quantification in tweets",
    author = "Abdou, Mostafa  and
      Kulmizev, Artur  and
      Gin{\'e}s i Ametll{\'e}, Joan",
    editor = "Apidianaki, Marianna  and
      Mohammad, Saif M.  and
      May, Jonathan  and
      Shutova, Ekaterina  and
      Bethard, Steven  and
      Carpuat, Marine",
    booktitle = "Proceedings of the 12th International Workshop on Semantic Evaluation",
    month = jun,
    year = "2018",
    address = "New Orleans, Louisiana",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/S18-1032/",
    doi = "10.18653/v1/S18-1032",
    pages = "210--217",
    abstract = "In this paper we describe our submission to SemEval-2018 Task 1: Affects in Tweets. The model which we present is an ensemble of various neural architectures and gradient boosted trees, and employs three different types of vectorial tweet representations. Furthermore, our system is language-independent and ranked first in 5 out of the 12 subtasks in which we participated, while achieving competitive results in the remaining ones. Comparatively remarkable performance is observed on both the Arabic and Spanish languages."
}