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SenticNet

  • Chapter
Sentic Computing

Part of the book series: Socio-Affective Computing ((SAC,volume 1))

Abstract

SenticNet is the knowledge base which the sentic computing framework leverages on for concept-level sentiment analysis. This chapter illustrates how such a resource is built. In particular, the chapter thoroughly explains the processes of knowledge acquisition, representation, and reasoning, which contribute to the generation of semantics and sentics that form SenticNet. The first part consists of a description of the knowledge sources used. The second part of the chapter illustrates how the collected knowledge is merged and represented redundantly at three levels: semantic network, matrix, and vector space. Finally, the third part presents the graph-mining and dimensionality-reduction techniques used to perform analogical reasoning, emotion recognition, and polarity detection.

Where there is no love, there is no understanding.

Oscar Wilde

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Notes

  1. 1.

    http://sentic.net/senticnet-3.0.zip

  2. 2.

    http://sentic.net/api

  3. 3.

    http://freebase.com

  4. 4.

    http://rtw.ml.cmu.edu/rtw

  5. 5.

    http://research.microsoft.com/probase

  6. 6.

    http://sentic.net/affectnet.zip

  7. 7.

    http://sentic.net/affectivespace.zip

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    Erik Cambria

  2. Computing Science and Mathematics, University of Stirling, Stirling, UK

    Amir Hussain

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Cambria, E., Hussain, A. (2015). SenticNet. In: Sentic Computing. Socio-Affective Computing, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-319-23654-4_2

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