Sentic API: A common-sense based API for concept-level sentiment analysis

• Main Authors: Cambria, Erik, Poria, Soujanya, Gelbukh, Alexander, Kwok, Kenneth
• Other Authors: School of Electrical and Electronic Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2017
• Subjects: Sentiment analysis; Natural language processing
• Online Access: https://hdl.handle.net/10356/84835; http://hdl.handle.net/10220/41976; http://ceur-ws.org/Vol-1141/
• Institution: Nanyang Technological University

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.