Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/84835
Title: Sentic API: A common-sense based API for concept-level sentiment analysis
Authors: Cambria, Erik
Poria, Soujanya
Gelbukh, Alexander
Kwok, Kenneth
Keywords: Sentiment analysis
Natural language processing
Issue Date: 2014
Source: Cambria, E., Poria, S., Gelbukh, A., & Kwok, K. (2014). Sentic API: A common-sense based API for concept-level sentiment analysis. CEUR Workshop Proceedings, 19-24.
Abstract: The bag-of-concepts model can represent semantics associated with natural language text much better than bags-of-words. In the bagof-words model, in fact, a concept such as cloud_computing would be split into two separate words, disrupting the semantics of the input sentence. Working at concept-level is important for tasks such as opinion mining, especially in the case of microblogging analysis. In this work, we present Sentic API, a common-sense based application programming interface for concept-level sentiment analysis, which provides semantics and sentics (that is, denotative and connotative information) associated with 15,000 natural language concepts.
URI: https://hdl.handle.net/10356/84835
http://hdl.handle.net/10220/41976
Rights: © 2014 The Author(s) (published by CEUR Workshop Proceedings). This paper was published in CEUR Workshop Proceedings and is made available as an electronic reprint (preprint) with permission of the author(s). The published version is available at: [http://ceur-ws.org/Vol-1141/]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Conference Papers

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