TY - GEN
T1 - CSL
T2 - 19th International Conference on Enterprise Information Systems, ICEIS 2017
AU - Moreno-Sandoval, Luis G.
AU - Beltrán-Herrera, Paola
AU - Vargas-Cruz, Jaime A.
AU - Sánchez-Barriga, Carolina
AU - Pomares-Quimbaya, Alexandra
AU - Alvarado-Valencia, Jorge A.
AU - García-Díaz, Juan C.
N1 - Publisher Copyright:
Copyright © 2017 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.
PY - 2017
Y1 - 2017
N2 - Opinion mining and sentiment analysis in texts from social networks such as Twitter has taken great importance during the last decade. Quality lexicons for the sentiment analysis task are easily found in languages such as English; however, this is not the case in Spanish. For this reason, we propose CSL, a Combined Spanish Lexicon approach for sentiment analysis that uses an ensemble of six lexicons in Spanish and a weighted bag of words strategy. In order to build CSL we used 68,019 tweets previously classified by researchers at the Spanish Society of Natural Language Processing (SEPLN) obtaining a precision of 62.05 and a recall of 60.75 in the validation set, showing improvements in both measurements. Additionally, we compare the results of CSL with a very well-known commercial software for sentiment analysis in Spanish finding an improvement of 10 points in precision and 15 points in recall.
AB - Opinion mining and sentiment analysis in texts from social networks such as Twitter has taken great importance during the last decade. Quality lexicons for the sentiment analysis task are easily found in languages such as English; however, this is not the case in Spanish. For this reason, we propose CSL, a Combined Spanish Lexicon approach for sentiment analysis that uses an ensemble of six lexicons in Spanish and a weighted bag of words strategy. In order to build CSL we used 68,019 tweets previously classified by researchers at the Spanish Society of Natural Language Processing (SEPLN) obtaining a precision of 62.05 and a recall of 60.75 in the validation set, showing improvements in both measurements. Additionally, we compare the results of CSL with a very well-known commercial software for sentiment analysis in Spanish finding an improvement of 10 points in precision and 15 points in recall.
KW - Opinion mining
KW - Polarity's classification
KW - Sentiment analysis
KW - Spanish Lexicon
KW - Spanish resources for sentiment analysis
UR - http://www.scopus.com/inward/record.url?scp=85023198205&partnerID=8YFLogxK
U2 - 10.5220/0006336402880295
DO - 10.5220/0006336402880295
M3 - Conference contribution
AN - SCOPUS:85023198205
T3 - ICEIS 2017 - Proceedings of the 19th International Conference on Enterprise Information Systems
SP - 288
EP - 295
BT - ICEIS 2017 - Proceedings of the 19th International Conference on Enterprise Information Systems
A2 - Hammoudi, Slimane
A2 - Smialek, Michal
A2 - Camp, Olivier
A2 - Filipe, Joaquim
A2 - Filipe, Joaquim
PB - SciTePress
Y2 - 26 April 2017 through 29 April 2017
ER -