Software review text fragments have considerably valuable information about users’ experience. It includes a huge set of properties including the software quality. Opinion mining or sentiment analysis is concerned with analyzing textual user judgments. The application of sentiment analysis on software reviews can find a quantitative value that represents software quality. Although many software...

The Federal Open Market Committee (FOMC) is a committee within the central banking system of the US and decides on the target rate. Analyzing the positions of its members is a challenge even for experts with a deep knowledge of the financial domain. In our work, we aim at automatically determining opinion groups in transcriptions of the FOMC discussions. We face two main challenges: first, the ...

-Sentiment analysis addresses the computational of feeling, sentiments and subjectivity in content, has reached an impressive consideration in recent years. Rather than the customary coarse-grained sentiment analysis tasks, for example document-level sentiment analysis. Aspect-oriented opinion mining aims to identify product aspects (features of products) about which opinion has been expressed ...

This paper describes our approaches to the opinion retrieval and blog distillation tasks for the Blog Track. For opinion retrieval we employ a two-stage framework consisting of keyword search and opinion classification, where customer reviews collected from Amazon.com are used for feature selection. For the blog distillation task we consider all the blog posts belonging to a blog in order to es...

In NTCIR-7 MOAT, we participated in four sub-tasks (opinion & holder detection, relevance judg-ment, and polarity classification) at two languagesides: Japanese and English. In this paper, we fo-cused on the feature selection and polarity classifi-cation methodology in both languages. To detectopinion and classify the polarity, the features wereselected based on a st...

While traditional information extraction systems have been built to answer questions about facts, subjective information extraction systems will answer questions about feelings and opinions. A crucial step towards this goal is identifying the words and phrases that express opinions in text. Indeed, although much previous work has relied on the identification of opinion expressions for a variety...

While most recent work has focused on instances of opinion spam which are manually identifiable or deceptive opinion spam which are written by paid writers separately, in this work we study both of these interesting topics and propose an effective framework which has good performance on both datasets. Based on the golden-standard opinion spam dataset, we propose a novel model which integrates s...

The tasks of feature-level opinion mining usually include the extraction of product entities from consumer reviews, the identification of opinion words that are associated with the entities, and the determining of these opinions’ polarities (e.g., positive, negative, or neutral). In recent years, two major approaches have been proposed to determine opinions at the feature level: model based met...

The recent surge in popularity of crowdsourcing has brought with it a new opportunity for engaging human intelligence in the process of data analysis. Crowdsourcing provides a fundamental mechanism for enabling online workers to participate in tasks that are either too difficult to be solved solely by a computer or too expensive to employ experts to perform. In the field of social science, four...