Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/20592
Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings
Author(s): Poria, Soujanya
Gelbukh, Alexander
Cambria, Erik
Yang, Peipei
Hussain, Amir
Durrani, Tariq
Contact Email: amir.hussain@stir.ac.uk
Title: Merging SenticNet and WordNet-Affect emotion lists for sentiment analysis
Citation: Poria S, Gelbukh A, Cambria E, Yang P, Hussain A & Durrani T (2012) Merging SenticNet and WordNet-Affect emotion lists for sentiment analysis. In: International Conference on Signal Processing Proceedings, ICSP. 2. 2012 IEEE 11th International Conference on Signal Processing (ICSP), Beijing, China, 21.10.2012-25.10.2012. Piscataway, NJ: IEEE, pp. 1251-1255. http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=6491803&abstractAccess=no&userType=inst; https://doi.org/10.1109/ICoSP.2012.6491803
Issue Date: 2012
Date Deposited: 9-Jul-2014
Series/Report no.: 2
Conference Name: 2012 IEEE 11th International Conference on Signal Processing (ICSP)
Conference Dates: 2012-10-21 - 2012-10-25
Conference Location: Beijing, China
Abstract: SenticNet is currently one of the most comprehensive freely available semantic resources for opinion mining. However, it only provides numerical polarity scores, while more detailed sentiment-related information for its concepts is often desirable. Another important resource for opinion mining and sentiment analysis is WordNet-Affect, which in turn lacks quantitative information. We report a work on automatically merging these two resources by assigning emotion labels to more than 2700 concepts.
Status: AM - Accepted Manuscript
Rights: Copyright 2012 IEEE. Publisher policy states that authors are free to post the accepted version of their article on their personal Web sites or those of their employers.
URL: http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=6491803&abstractAccess=no&userType=inst

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