Sentiment analysis is essential in many real-world applications such as stance detection,
review analysis, recommendation system, and so on. Sentiment analysis becomes more …

The paper describes the usage of self-learning Hierarchical LSTM technique for classifying
hatred and trolling contents in social media code-mixed data. The Hierarchical LSTM-based …

Indians and many other non-English speakers across the world, prefer not to use single
code in their messaging texts on social media platforms. They make use of transliteration …

Hate speech detection in social media texts is an important Natural language Processing
task, which has several crucial applications like sentiment analysis, investigating …

Analyzing explicit and clear sentiment is challenging owing to the growing use of
emblematic and multilingual language constructs. This research proposes sarcasm …

Abstract Language is a social phenomenon and variation is inherent to its social nature.
Recently, there has been a surge of interest within the computational linguistics (CL) …

This paper describes the development of a multilingual, manually annotated dataset for
three under-resourced Dravidian languages generated from social media comments. The …

Training language models for Code-mixed (CM) language is known to be a difficult problem
because of lack of data compounded by the increased confusability due to the presence of …

Code-switching, the alternation of languages within a conversation or utterance, is a
common communicative phenomenon that occurs in multilingual communities across the …

Sentiment analysis (SA) using code-mixed data from social media has several applications
in opinion mining ranging from customer satisfaction to social campaign analysis in …