Lexicon based sentiment analysis usually relies on the identification of various words to
which a numerical value corresponding to sentiment can be assigned. In principle …

Data annotation is a critical step to train a text model but it is tedious, expensive and time-
consuming. We present a language independent method to train a sentiment polarity model …

Abstract Sentiment Analysis at Document Level is a well-known problem in Natural
Language Processing (NLP), being considered as a reference in NLP, over which new …

Nowadays, businesses and organizations are very eager to analyze emotional tendencies
of the information generated by the consumers on the internet. Most of the current …

The development of numerous feature extraction techniques, ranging from conventional to
advanced, targeted at improving the accuracy of sentiment categorization, has been sparked …

With the development of the Internet, various social media have attracted many people to
share their thoughts and describe their feelings. Most of these comments are emotional. In …

Sentiment analysis is a wildly studied topic in Natural Language Processing (NLP) area.
Most researchers focus on the model and algorithm of text processing regardless of other …

Unstructured text data produced on the internet grows rapidly, and sentiment analysis for
short texts becomes a challenge because of the limit of the contextual information they …

Sentiment analysis is a significant task in nature language processing (NLP). Acquiring high
quality word representations is a key point in the task. Specially we find that the same word …

Code-mixing is a phenomenon which arises mainly in multilingual societies. Multilingual
people, who are well versed in their native languages and also English speakers, tend to …