Now-a-days due to the rapid growth of internet, people are expressing their views and opinions regarding, products, services and policies on the web in large numbers. This huge amount of feedback is very crucial for both organizations as well as individuals. The task of analysing these reviews is done by Opinion Mining (also known as Semantic Analysis). It aims for distinguishing the emotions e...

Opinion mining is a field of Natural Language Processing (NLP) that used to carry out the process extracting and processing textual data which functions obtain information through sentiment analysis from document in form text, among others, detect attitudes towards objects or people. Sub-processes opinion can use documents subjectivity, orientation, detection targets find as analysis, aims asse...

In the last few years as the growth & use of Internet increases and share of user’s opinions increases, the inspiration towards opinion mining also increases. When person wants to conduct some research or making day to day decisions, he has to depend on other people’s opinions. We consult “political discussion forums when going to a political vote, read consumer reports when purchasing some pro...

In this paper, opinion polarity classification on news texts has been carried out for a less privileged language Bengali using Support Vector Machine (SVM) 1 . The present system identifies semantic orientation of an opinionated phrase as either positive or negative. The classification of text as either subjective or objective is clearly a precursor to determine the opinion orientation of evalu...

Collaborative Working Environments (CWE) are widely used for effective collaboration among users. A CWE includes various tools and methodologies to support analysis of coordinating activities. Users within a CWE widely utilize textual means of collaboration and communication. An effective analysis of this textual collaboration can help in improving overall quality of collaborating activities an...

Aspect-based opinion mining has attracted lots of attention today. In this paper, we address the problem of product aspect rating prediction, where we would like to extract the product aspects, and predict aspect ratings simultaneously. Topic models have been widely adapted to jointly model aspects and sentiments, but existing models may not do the prediction task well due to their weakness in ...

Multilingual Opinion Mining deals with the analysis of opinions, regardless of the language in which they are written. Works in this area focus on the classification of the polarity of opinions extracted from texts, and less attention has been paid to the classification of emotions. This work proposes the use of Multilingual Opinion Mining techniques for emotion mining using parallel corpora. W...

Sentiment classification is a fundamental task in opinion mining. However, most existing systems require a sentiment lexicon to guide sentiment classification, which inevitably suffer from the problem of unknown words. In this paper, we present a morpheme-based fine-to-coarse strategy for Chinese sentence-level sentiment classification. To approach this, we first employ morphological productivi...

We present on-going work on the harmonization of existing German lexical resources in the field of opinion and sentiment mining. The input of our harmonization effort consisted in four distinct lexicons of German word forms, encoded either as lemmas or as full forms, marked up with polarity features, at distinct granularity levels. We describe how the lexical resources have been mapped onto eac...

Opinion mining on Twitter recently attracted research interest in politics using Information Retrieval (IR) and Natural Language Processing (NLP). However, getting domain-specific annotated data still remains a costly manual step. In addition, the amount and quality of these annotation may be critical regarding the performance of machine learning (ML) based systems. An alternative solution is t...