Sentiment analysis is part of Natural Language Processing (NLP) area and it is the process of identifying and extracting subjective information from text. 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/consumers express and opinion. Sentiment analysis aims to determine the attitude of a writer in a document by means of Machine Learning approaches.

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. This topic is of particular interest for user of monitoring tool for detecting on complex/high-dimensional dataset the topics where the writer's polarity is more different from a particular clustering to another. 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.


HIT Research Centre will be involved in:
- Defining appropriate market domains for the research investigations
- Identifying target entities
- Defining datasets format
- Developing algorithms and procedures for aspect term/category extraction
- Developing algorithms and procedures for aspect term/category polarity
- Testing the algorithms performance
- Validating the procedure in a Support Decision System framework"

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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