Bueno García, ItzcoatlCarrasco González, Ramón AlbertoUreña, RaquelHerrera-Viedma, Enrique2025-01-142025-01-142022Bueno, I., Carrasco, R. A., Ureña, R., & Herrera-Viedma, E. (2022). A business context aware decision-making approach for selecting the most appropriate sentiment analysis technique in e-marketing situations. Information Sciences, 589, 300–320. https://doi.org/10.1016/J.INS.2021.12.08010.1016/j.ins.2021.12.080https://hdl.handle.net/20.500.14352/114165In the era of social media, consumers interact and exchange information, subjective opin ions, feelings or thoughts about a given issue, a product or a service, via Web 2.0 technolo gies. As a result, electronic Word of Mouth, eWOM, has gained increasing influence on the formation of user opinions. Therefore, extracting and analyzing eWOM statements by means of Sentiment Analysis techniques is currently a hot topic that could potentially pro vide companies with key information about their customers. However, among all the avail able techniques, choosing the most appropriate one according to the analysis criteria is a real challenge. In this contribution, we first study the main desirable criteria for a senti ment analysis approach and classify the different existing approaches based on these cri teria to try and provide a solution to this issue. We then propose a Multi-criteria Decision-Making methodology that selects the most suitable technique for each business case by taking their particular criteria into account.engAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/journal articlehttps://doi.org/10.1016/j.ins.2021.12.080open access519.862.6658.8:004.738.5339:077Sentiment analysisAHPMulti-Criteria Decision-MakingAuto machine learningEconometría (Estadística)Marketing5302 Econometría5311.05 Marketing (Comercialización)