The preprocessing pipelines in Natural Language Processing usually involve a step of
removing sentences consisted of illegal characters. The definition of illegal characters and …

In synonym replacement-based data augmentation techniques for natural language
processing tasks, words in a sentence are often sampled randomly with equal probability. In …

In this chapter, we will perform sentiment analysis from text data. Generally, sentiment
analysis is performed based on the processing of natural language, the analysis of text and …

Semantic word representations have been very useful but usually ignore the syntactic
relationship. In the task of sentiment analysis, compositional vector representations require …

Sentiment analysis methods co-ordinate text mining components, such as sentence splitters,
tokenisers and classifiers, into pipelined applications to automatically analyse the emotions …

Our challenge is gaining insight, analyzing and understanding implicit behavior behind text.
Useful tools are machine learning and sentiment analysis. Text classification copes with …

Sentiment analysis or opinion mining seeks to automate the detection of subjectiveness
underlying a text. It is essential for many applications, such as political campaign, online …

For many years, researchers in the field of natural language processing have been
exploring sentiment analysis, a method for understanding human feelings and thoughts …

One of the benefits of recognizing a slang, an id-iom or an abbreviation in a tweet is the
ability to help in finding certain sentiment in a concise and understandable manner …

Although many sentiment lexicons in different languages exist, most are not comprehensive.
In a recent sentiment analysis application, we used a large Chinese sentiment lexicon and …