opinion mining deals with an analysis of user reviews for extracting their opinions, sentiments and demands in a specific area, which can play an important role in making major decisions in such area. in general, opinion mining extracts user reviews at three levels of document, sentence and feature. opinion mining at the feature level is taken into consideration more than the other two levels d...

rapid growth of networks and social networks results in more access to people’s opinion. these opinions contain useful information. by analyzing these opinions, people’s preferences and their positive and negative opinions about different subjects can be identified. opinion mining is the process of analyzing people’s emotions, feelings and opinions to identify their preferences. in this article...

Opinion mining deals with an analysis of user reviews for extracting their opinions, sentiments and demands in a specific area, which can play an important role in making major decisions in such area. In general, opinion mining extracts user reviews at three levels of document, sentence and feature. Opinion mining at the feature level is taken into consideration more than the other two levels d...

Given a controversial issue, argument mining from natural language texts (news papers, and any form of text on the Internet) is extremely challenging: domain knowledge is often required together with appropriate forms of inferences to identify arguments. This contribution explores the types of knowledge that are required and how they can be paired with reasoning schemes, language processing and...

In this paper we demonstrate approaches for opinion mining in Latvian text. Authors have applied, combined and extended results of several previous studies and public resources to perform opinion mining in Latvian text using two approaches, namely, semantic polarity analysis and machine learning. One of the most significant constraints that make application of opinion mining for written content...

Emotion lexicons play a crucial role in sentiment analysis and opinion mining. In this paper, we propose a novel Emotion-aware LDA (EaLDA) model to build a domainspecific lexicon for predefined emotions that include anger, disgust, fear, joy, sadness, surprise. The model uses a minimal set of domain-independent seed words as prior knowledge to discover a domainspecific lexicon, learning a fine-...

Sentiment analysis and opinion mining are actively explored nowadays. One of the most important resources for the sentiment analysis task is sentiment lexicon. This paper presents our study in building domain-specific sentiment lexicon for Indonesian language. Our main contributions are (1) methods to expand sentiment lexicon using sentiment patterns and (2) a technique to classify the polarity...

Sentiment analysis aims to identify and categorize customer’s opinion and judgments using either traditional supervised learning techniques or unsupervised approaches. Traditionally, Sentiment Analysis is performed using machine learning techniques such as a naive Bayes classification or support vector machines (SVM), or could make use of a sentiment lexicon, that is, a list of words that are m...

Text on the web has become a valuable source for mining and analyzing user opinions on any topic. Non-native English speakers heavily support the growing use of Network media especially in Chinese. Many sentiment analysis studies have shown that a polarity lexicon can effectively improve the classification consequences. Social media, where users spontaneously generated content have become impor...