Connotation Lexicon:
A Dash of Sentiment Beneath the Surface Meaning

Understanding the connotation of words plays an important role in interpreting subtle shades of sentiment beyond denotative or surface meaning of text, as seemingly objective statements often allude nuanced sentiment of the writer, and even purposefully conjure emotion from the readers’ minds. The focus of our work is drawing nuanced, connotative sentiments from even those words that are objective on the surface, such as “intelligence”, “human”, and “cheesecake”. We developed induction algorithms encoding a diverse set of linguistic insights (semantic prosody, distributional similarity, semantic parallelism of coordination) and prior knowledge drawn from lexical resources, resulting in the first broad-coverage connotation lexicon.


Online Search

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Relevant Papers

Connotation Lexicon: A Dash of Sentiment Beneath the Surface Meaning. Song Feng, Jun Seok Kang, Polina Kuznetsova and Yejin Choi. Association for Computational Linguistics (ACL), 2013. [pdf]

Learning General Connotation of Words using Graph-based Algorithms. Song Feng, Ritwik Bose, and Yejin Choi. Empirical Methods in Natural Language Processing (EMNLP) , 2011. [pdf]

Citation: please cite the following if using our connotation lexicon.

	author    = {Feng, Song  and  Kang, Jun Sak and Kuznetsova, Polina  and  Choi, Yejin},
	title     = {Connotation Lexicon: A Dash of Sentiment Beneath the Surface Meaning},
	booktitle = {Proceedings of the 51th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)},
	month     = {Angust},
	year      = {2013},
	address   = {Sofia, Bulgaria},
	publisher = {Association for Computational Linguistics},


We will also make annotated labels from Amazon Mechanical Turk available soon.

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