Sentiment Analysis on Tweets about Diabetes: An Aspect-Level Approach

Abstract EN

In recent years, some methods of sentiment analysis have been developed for the health domain; however, the diabetes domain has not been explored yet.

In addition, there is a lack of approaches that analyze the positive or negative orientation of each aspect contained in a document (a review, a piece of news, and a tweet, among others).

Based on this understanding, we propose an aspect-level sentiment analysis method based on ontologies in the diabetes domain.

The sentiment of the aspects is calculated by considering the words around the aspect which are obtained through N-gram methods (N-gram after, N-gram before, and N-gram around).

To evaluate the effectiveness of our method, we obtained a corpus from Twitter, which has been manually labelled at aspect level as positive, negative, or neutral.

The experimental results show that the best result was obtained through the N-gram around method with a precision of 81.93%, a recall of 81.13%, and an F-measure of 81.24%.