Sentic API: A common-sense based API for concept-level sentiment analysis
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-leve...
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| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2017
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/84835 http://hdl.handle.net/10220/41976 http://ceur-ws.org/Vol-1141/ |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | 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. |
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