Markets are paying greater attention to the emotional aspects of communication.
Sentiment analysis is part of Natural Language Processing (NLP) area and it is the process of identifying and extracting subjective information from text.
Knowing if users are happy when they talk about a brand is extremely important for creating optimal marketing strategies, in fact the advantages of using this technology allow you to create personalized advertising customized.
Sentiment analysis is widely applied in web-related applications, for the monitoring of social media and, in general, for the monitoring of all contents where people express an opinion.
All the innovative companies actually use this kind of tools to detect the emotions of their users in order to align with the development of opinions.
Sentiment analysis aims to determine the attitude of a writer in a document by means of Machine Learning approaches.
This software analyzes text conversations and evaluates the tone, intent, emotions behind each message, helping the customer service team in analyzing consumer feedback.
Aspect Based Sentiment Analysis (ABSA) is a new research area of NLP that aims to detect the polarity of a written text in regards to a particular aspect/feature.

Thanks to this type of analysis we can improve the understanding of customer needs and so anticipate opportunities, drivers, trends and market challenges.
While some approaches have been presented to deal with this task, many issues are still unanswered: for example, the portability of a methodology from one language to another and the need of tagged text to perform the algorithm training.
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Project Start Date: 1st May 2016
Project Duration: 28th Feb 2017
Project Coordinator: Alessandro Beghi
Total Project Funding: 35.200,00 €
Partners: Statwolf LTD 
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