Automatically identifying a software product´s quality attributes through sentiment analysis of tweets

Software quality attributes can be identified based on software features such as security, reliability and user-friendliness. This process can be done either manually or automatically. Sentiment analysis refers to the sentiment extraction task from resources such as natural language texts. We study the application of sentiment analysis on extracting the quality attributes of a software product based on the opinions of end-users that have been stated in microblogs such as Twitter. Our findings obtain advantageous techniques such as document frequency of words in a large number of tweets. The extracted results can help software developers know the advantages and disadvantages of their products.