In this paper, we propose a general framework that allows developers to filter, summarize and analyze user reviews written about applications on App Stores. Our framework extracts automatically relevant features from reviews of apps (e.g., information about functionalities, bugs, requirements, etc) and analyzes the sentiment associated with each of them. Our framework has three main building blocks, namely, (i) topic modeling, (ii) sentiment analysis and (iii) summarization interface. The topic modeling block aims at finding semantic topics from textual comments, extracting the target features based on the most relevant words of each discovered topic. The sentiment analysis block detects the sentiment associated with each discovered feature. The summarization interface provides to developers an intuitive visualization of the features (i.e., topics) and their associated sentiment, providing richer information than a 'star rating' strategy. Our evaluation shows that the topic modeling block is able to organize information provided by users in subcategories that facilitate the understanding of which features more positively/negatively impact the overall evaluation of the application. Regarding user satisfaction, we can observe that, in spite of the star rating being a good measure of evaluation, the Sentiment Analysis technique is more accurate in capturing the sentiment transmitted by the user by means of a comment.

Ontologies, since its formal definition in the 90's up to its effective usage with the advent of methods and processes from the Ontology Engineering, have received important attention in projects that demand the formalization of shared knowledge among applications and users. In this context, it is important to popularize and to make people able to create and use them. This article presents an ontology capture method, providing apparatus to conceptualize and identify the treated domain. The proposed method is capable to provide metrics and guidelines so that an ontology engineer can identify and organize the elements of a domain, finding fundamental ontological relations among them. A descriptive algorithm is shown to formalize the wished process and some examples are given to better exemplify the utilization of the proposed ontology capture method.