Leveraging semantics for sentiment polarity detection in social media-Reference-Cited by-同舟云学术

Leveraging semantics for sentiment polarity detection in social media

Published:2017-09-19 Issue:8 Volume:10 Page:2045-2055
ISSN:1868-8071
Container-title:International Journal of Machine Learning and Cybernetics
language:en
Short-container-title:Int. J. Mach. Learn. & Cyber.

Author:

Dridi Amna,Reforgiato Recupero Diego^ORCID

Funder

Sardinia Regional Government

EU Commission

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

http://link.springer.com/content/pdf/10.1007/s13042-017-0727-z.pdf

Reference41 articles.

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3. Barbosa L, Feng J (2010) Robust sentiment detection on twitter from biased and noisy data. In: Proceedings of COLING, pp 36–44

4. Cambria E, Grassi M, Hussain A, Havasi C (2012) Sentic computing for social media marketing. Multimed Tools Appl 59(2):557–577

5. Cambria E, Poria S, Bajpai R, Schuller BW (2016) SenticNet 4: a semantic resource for sentiment analysis based on conceptual primitives. Proc COLING 2016:2666–2677

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