@inproceedings{sharma-bhattacharyya-2016-high,
    title = "High, Medium or Low? Detecting Intensity Variation Among polar synonyms in {W}ord{N}et",
    author = "Sharma, Raksha  and
      Bhattacharyya, Pushpak",
    editor = "Fellbaum, Christiane  and
      Vossen, Piek  and
      Mititelu, Verginica Barbu  and
      Forascu, Corina",
    booktitle = "Proceedings of the 8th Global WordNet Conference (GWC)",
    month = "27--30 " # jan,
    year = "2016",
    address = "Bucharest, Romania",
    publisher = "Global Wordnet Association",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/2016.gwc-1.54/",
    pages = "389--395",
    abstract = "For fine-grained sentiment analysis, we need to go beyond zero-one polarity and find a way to compare adjectives (synonyms) that share the same sense. Choice of a word from a set of synonyms, provides a way to select the exact polarity-intensity. For example, choosing to describe a person as benevolent rather than kind1 changes the intensity of the expression. In this paper, we present a sense based lexical resource, where synonyms are assigned intensity levels, viz., high, medium and low. We show that the measure P (s|w) (probability of a sense s given the word w) can derive the intensity of a word within the sense. We observe a statistically significant positive correlation between P(s|w) and intensity of synonyms for three languages, viz., English, Marathi and Hindi. The average correlation scores are 0.47 for English, 0.56 for Marathi and 0.58 for Hindi."
}