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# Sentiment Analysis  ## \cite{Serrano-Guerrero2015}: Sentiment analysis: A review and comparative analysis of web services - opinions, sentiments, appraisals, attitudes, and emotions, which are the focus of Sentiment Analysis  - extraction of sentiments, sentiment classification, subjectivity classification, opinion summarization or opinion spam detection, among others  - present a detailed description of a set of 15 well-known free access services focused on Sentiment Analysis  - subjectivity classification (useful)?  - multi-document summarization once features and entities have been detected, the system has to group and/or order the different sentences which express sentiments related to those entities or features. The final summary can be presented as a graphic or a text showing the main features/entities and quantifying the sentiment with regard to each one in some way, for example, aggregating intensities of sentiments or counting the number of positive or negative sentences [9,67,69,63,62,23,24,85].  - Platforms:  - Lymbix goes further than a simple sentiment classification (positive, negative or neutral categories), it measures the emo-  tive context in social conversations through different concepts grouped into different positive or negative categories.  - Opendover is an ontology-based service specialized in different domains such as education, law, politics, health, economy, and ecology.  - Semantria the system is flexible and allows the user to insert his own dictionary with the associated weights for each word included.  - Sentimetrix: allows learning types of words people use to express emotions, for example, emoticons, slang, hashtags, etc.  - Uclassify: language detection, text gender and age recog-  nition (if a text is written by a male or female and his/her age), spam filter, Sentiment Analysis, document tagging, emotion detection, among others.