Towards a unified framework for opinion retrieval, mining and summarization

Abstract

The exponential increase of subjective, user-generated content since the birth of the Social Web, has led to the necessity of developing automatic text processing systems able to extract, process and present relevant knowledge. In this paper, we tackle the Opinion Retrieval, Mining and Summarization task, by proposing a unified framework, composed of three crucial components (information retrieval, opinion mining and text summarization) that allow the retrieval, classification and summarization of subjective information. An extensive analysis is conducted, where different configurations of the framework are suggested and analyzed, in order to determine which is the best one, and under which conditions. The evaluation carried out and the results obtained shows the appropriateness of the individual components, as well as the framework as a whole. By achieving an improvement over 10% compared to the state-of-the-art approaches in the context of blogs, we can conclude that subjective text can be efficiently dealt with by means of our proposed framework.

Opinion Mining and Summarization of Hotel Reviews

“…Classification algorithms such as Naive Bayes [11], SVM [4], and Decision Tree [1] work well for review text. Other methods such as resource based opinion mining [6], [7] also proposed by different researchers. It depends upon resources such as SentiWordNet [10], WordNet Affect [14] which contain polarity values of word for sentiment classification.…”

“…Some researchers suggested Text summarization approaches [6] for opinion summarization of review text. Authors also proposed aspect based summarization of product reviews in [11] [12].…”

“…Opinion mining is classification of user's expressed opinion into positive or negative polarity. Opinion summarization is a process of representation of review information in short and summarized form [6]. It also involves selecting important aspects and representing related expressed opinions from reviews.…”

Untitled

“…To help us find a way through this abundance the recent decade has brought a boom in developing automatic text processing systems, which are able to extract, process and present relevant knowledge (Lloret et al 2012). One of these systems is Sentiment Analysis (SA) 1 , whose main goal is to determine whether a text, or a part of it, is subjective or not and, if subjective, whether it expresses a positive or negative view (Taboada 2016).…”

Framework for Participative and Collaborative Governance using Social Media Mining Techniques

“…Since the unlabeled data are easier to obtain, techniques that make use of the positive and unlabeled data for learning are examined [6]. Text mining techniques for mining sentiments and opinions from social media are used [7,12].…”