Abstract
The social networks proliferation over the Internet has generated an interest from the users to express communicate and make opinions about different topics, services or people. This has led the creation of tools, methods, techniques and models that are enable to obtain information from the web in order to analyze and identify the emotion that is shown by the users in their opinions, this has given the key to the development and improvement of sentimental semantic lexicons to the emotional analysis in opinions. This paper shows the proposal of the Model to Analyze Emotions in subjective social corpus through the adaptation of an affective semantic lexicon, focused on the extension of an affective lexicon in order to adequate to the Spanish spoken in Mexico considering the linguistic variations.
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Gutiérrez, G. et al. (2014). A Sentiment Analysis Model: To Process Subjective Social Corpus through the Adaptation of an Affective Semantic Lexicon. In: Gelbukh, A., Espinoza, F.C., Galicia-Haro, S.N. (eds) Human-Inspired Computing and Its Applications. MICAI 2014. Lecture Notes in Computer Science(), vol 8856. Springer, Cham. https://doi.org/10.1007/978-3-319-13647-9_22
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DOI: https://doi.org/10.1007/978-3-319-13647-9_22
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