Sentiment shifters, i.e., words and expressions that can affect text polarity, play an important role in opinion mining. However, the limited ability of current automated opinion mining systems to handle shifters represents a major challenge. The majority of existing approaches rely on a manual list of shifters; few attempts have been made to automatically identify shifters in text. Most of the...

Opinion mining aims at extracting useful subjective information from reliable amounts of text. Opinion mining holder recognition is a task that has not been considered yet in Arabic Language. This task essentially requires deep understanding of clauses structures. Unfortunately, the lack of a robust, publicly available, Arabic parser further complicates the research. This paper presents a leadi...

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-...

Analysis of opinions, known as opinion mining or sentiment analysis, has attracted a great deal of attention recently due to many practical applications and challenging research problems. In this article, we study two important problems, namely, opinion lexicon expansion and opinion target extraction. Opinion targets (targets, for short) are entities and their attributes on which opinions have ...

Fine grained opinion mining is an important task in today’s E-business world. Customers and manufacturers wanted to know about products in details. So in this paper we have studied opinion targets and opinion word extraction through dependency parsing and by applying syntactic patterns. Previously developed double propagation approach is useful for extraction task with addition of some syntacti...

The main focus of this paper is to investigate methods for opinion extraction at a more detailed level of granularity, retrieving not only the opinionated portion of text, but also the target of that expressed opinion. We describe a novel approach to fine-grained opinion mining that, after an initial lexicon based processing step, treats the problem of finding the opinion expressed towards an e...

with the exponential growth of social media i.e. blogs and social networks, organizations and individual persons are increasingly using the number of reviews of these media for decision making about a product or service. Opinion mining detects whether the emotions of an opinion expressed by a user on Web platforms in natural language, is positive or negative. This paper presents extensive exper...

This technical report presents the work carried out at the University of Lugano on TREC 2014 Federated Web Search track. The main motivation behind our approach is to provide better coverage of opinions that are present in federated resources. On the resource selection and vertical selection steps, we apply opinion mining to select opinionated resources/verticals given a user’s query. We do thi...

The success of Information technologies and associated services (e.g., blogs, forums,...) eases the way to express massive opinion on various topics. Recently new techniques known as opinion mining have emerged. One of their main goals is to automatically extract a global trend from expressed opinions. While it is easy to get this overall assessment, a more detailed analysis will highlight that...

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...