Abstract
In the last years, different efforts have been made to extract information that users express through online social networking services, e.g. Twitter. Despite the progress achieved, there are still open gaps to be addressed. Related to the sentiment analysis issue, we stand out the following gaps: (a) low accuracy in sentiment classification task for short texts; and, (b) lack of tools for sentiment analysis in several languages. Aiming to fill these gaps, in this paper we apply the Spanish adaptation of ANEW (Affective Norms for English Words) as resource to improve the Twitter sentiment analysis by applying a variety of multi-label classifiers in a corpus of Spanish tweets collected by us. To the best of our knowledge, this is the first work using a Spanish adaptation of ANEW for sentiment analysis.
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References
Bobicev, V.: Text classification: the case of multiple labels. In: 2016 International Conference on Communications (COMM), pp. 39–42. IEEE (2016)
Bradley, M.M., Lang, P.J.: Affective norms for English words (ANEW): Instruction manual and affective ratings. Technical report. Citeseer (1999)
Cherman, E.A., Spolaôr, N., Valverde-Rebaza, J., Monard, M.C.: Lazy multi-label learning algorithms based on mutuality strategies. J. Intell. Robot. Syst. 80(1), 261–276 (2015)
Metz, J., de Abreu, L.F.D., Cherman, E.A., Monard, M.C.: On the estimation of predictive evaluation measure baselines for multi-label learning. In: Pavón, J., Duque-Méndez, N.D., Fuentes-Fernández, R. (eds.) IBERAMIA 2012. LNCS (LNAI), vol. 7637, pp. 189–198. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-34654-5_20
Miranda, C.H., Guzman, J.: A review of sentiment analysis in Spanish. Tecciencia 12(22), 35–48 (2017)
Montefinese, M., Ambrosini, E., Fairfield, B., Mammarella, N.: The adaptation of the affective norms for English words (ANEW) for Italian. Behav. Res. Methods 46(3), 887–903 (2014)
Nielsen, F.Å.: A new ANEW: evaluation of a word list for sentiment analysis in microblogs. arXiv preprint arXiv:1103.2903 (2011)
Raja, M., Swamynathan, S.: Tweet sentiment analyzer: sentiment score estimation method for assessing the value of opinions in tweets. In: Proceedings of the International Conference on Advances in Information Communication Technology & Computing, p. 83. ACM (2016)
Redondo, J., Fraga, I., Padrón, I., Comesaña, M.: The Spanish adaptation of ANEW (affective norms for English words). Behav. Res. Methods 39(3), 600–605 (2007)
Soares, A.P., Comesaña, M., Pinheiro, A.P., Simões, A., Frade, C.S.: The adaptation of the affective norms for English words (ANEW) for European Portuguese. Behav. Res. Methods 44(1), 256–269 (2012)
Spyromitros, E., Tsoumakas, G., Vlahavas, I.: An empirical study of lazy multilabel classification algorithms. In: Darzentas, J., Vouros, G.A., Vosinakis, S., Arnellos, A. (eds.) SETN 2008. LNCS (LNAI), vol. 5138, pp. 401–406. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-87881-0_40
Tellez, E.S., Miranda-Jiménez, S., Graff, M., Moctezuma, D., Siordia, O.S., Villaseñor, E.A.: A case study of Spanish text transformations for twitter sentiment analysis. Expert Syst. Appl. 81, 457–471 (2017)
Zhang, M.L., Zhou, Z.H.: A k-nearest neighbor based algorithm for multi-label classification. In: 2005 IEEE International Conference on Granular Computing, vol. 2, pp. 718–721. IEEE (2005)
Zhao, Y., Qin, B., Liu, T., Tang, D.: Social sentiment sensor: a visualization system for topic detection and topic sentiment analysis on microblog. Multimedia Tools Appl. 75(15), 8843–8860 (2016)
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We would like to thank psychologist María Soledad Silva for her collaboration.
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Palomino, R., Meléndez, C., Mauricio, D., Valverde-Rebaza, J. (2019). ANEW for Spanish Twitter Sentiment Analysis Using Instance-Based Multi-label Learning Algorithms. In: Lossio-Ventura, J., Muñante, D., Alatrista-Salas, H. (eds) Information Management and Big Data. SIMBig 2018. Communications in Computer and Information Science, vol 898. Springer, Cham. https://doi.org/10.1007/978-3-030-11680-4_6
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