Aspect-Based Sentiment Analysis (ABSA) is an advanced NLP application that aims to identify aspect terms present in the given review and predict sentiment associated with those terms. ABSA better than sentence-based classification because it considers reviews determine rather considering individual sentence. Entrepreneurs could make use of understand customers' opinions about different aspects ...

Traditionally, businesses spend tons of money performing customer surveys on brands. In the big data age, such insights including both consumer compliments and complaints can be automatically collected from social media such as twitter. The enabling technology is sentiment analysis. It is observed that social media often uses emoticons such as :) and :( mixed with text to express sentiment. Thi...

Multimodal sentiment analysis is an increasingly popular research area, which extends the conventional language-based definition of sentiment analysis to a multimodal setup where other relevant modalities accompany language. In this paper, we pose the problem of multimodal sentiment analysis as modeling intra-modality and inter-modality dynamics. We introduce a novel model, termed Tensor Fusion...

The massive amount of data in social media platforms is a key source for companies to analyze customer sentiment and opinions. Many existing sentiment analysis approaches solely rely on textual contents of a sentence (e.g. words) for sentiment identification. Consequently, current sentiment analysis systems are ineffective for analyzing contents in social media because people may use non-standa...

We investigated the pairing of a financial news article prediction system, AZFinText, with sentiment analysis techniques. From our comparisons we found that news articles of a subjective nature were easier to predict in both price direction (59.0% vs 50.4% without sentiment) and through a simple trading engine (3.30% return vs 2.41% without sentiment). Looking into sentiment further, we found t...

Sentiment Analysis in the Arabic Language Using Machine Learning Sentiment analysis has recently become one of the growing areas of research related to natural language processing and machine learning. Much opinion and sentiment about specific topics are available online, which allows several parties such as customers, companies and even governments, to explore these opinions. The first task is...

Sentiment analysis is an important step towards comprehension in natural language processing. Movie reviews are a convenient source of highly polarized sentences for use in sentiment analysis. Achieving a high level of accuracy in the sign of nonneutral sentiment is a challenge. When the problem is expanded to choosing one of 5 sentiment levels the problem becomes significantly harder. Among th...

This paper presents two vector representations proposed by National Chiayi University (NCYU) about phrased-based sentiment detection which was used to compete in dimensional sentiment analysis for Chinese phrases (DSACP) at IJCNLP 2017. The vector-based sentiment phraselike unit analysis models are proposed in this article. E-HowNet-based clustering is used to obtain the values of valence and a...

Sentiment classification is an ongoing field and interesting area of research because of its application in various fields collecting review from people about products and social and political events through the web. Currently, Sentiment Analysis concentrates for subjective statements or on subjectivity and overlook objective statements which carry sentiment(s). During the sentiment classificat...

Sentiment analysis of citations in scientific papers is a new and interesting problem which can open up many exciting new applications in bibliometrics. Current research assumes that using just the citation sentence is enough for detecting sentiment. In this paper, we show that this approach misses much of the existing sentiment. We present a new corpus in which all mentions of a cited paper ha...