Text mining in big data analytics is emerging as a powerful tool for harnessing the power of
unstructured textual data by analyzing it to extract new knowledge and to identify significant …

As the prevalence of social media on the Internet, opinion mining has become an essential
approach to analyzing so many data. Various applications appear in a wide range of …

The extraction of useful insights from text with various types of statistical algorithms is
referred to as text mining, text analytics, or machine learning from text. The choice of …

With the increasing development of Web 2.0, such as social media and online businesses,
the need for perception of opinions, attitudes, and emotions grows rapidly. Sentiment …

The tasks in fine-grained opinion mining can be regarded as either a token-level sequence
labeling problem or as a semantic compositional task. We propose a general class of …

Sentiment analysis and opinion mining is the field of study that analyzes people's opinions,
sentiments, evaluations, attitudes, and emotions from written language. It is one of the most …

Sentiment analysis or opinion mining is the computational study of people's opinions,
appraisals, attitudes, and emotions toward entities, individuals, issues, events, topics and …

We present an approach to detecting hate speech in online text, where hate speech is
defined as abusive speech targeting specific group characteristics, such as ethnic origin …

A clinical sentiment is a judgment, thought or attitude promoted by an observation with
respect to the health of an individual. Sentiment analysis has drawn attention in the …

Sentiment analysis on Twitter data has attracted much attention recently. In this paper, we
focus on target-dependent Twitter sentiment classification; namely, given a query, we …