Abstract Textual Emotion Analysis (TEA) aims to extract and analyze user emotional states
in texts. Various Deep Learning (DL) methods have developed rapidly, and they have …

Big data has become a significant research area due to the birth of enormous data
generated from various sources like social media, internet of things and multimedia …

Sentiment analysis is one of the prominent fields of data mining that deals with the
identification and analysis of sentimental contents generally available at social media …

A large community of research has been developed in recent years to analyze social media
and social networks, with the aim of understanding, discovering insights, and exploiting the …

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

Nonprofits offer services to disadvantaged populations, mobilize collective action, and
advocate for civil rights. Conducting this work requires significant resources, raising the …

The complexity that characterises the dynamic nature of the various environmental factors
makes it very compelling for firms to be capable of addressing the changing customers' …

Affective computing is an emerging multidisciplinary research field that is increasingly
drawing the attention of researchers and practitioners in various fields, including artificial …

In recent times, data is growing rapidly in every domain such as news, social media,
banking, education, etc. Due to the excessiveness of data, there is a need of automatic …

Predicting context-dependent and non-literal utterances like sarcastic and ironic
expressions still remains a challenging task in NLP, as it goes beyond linguistic patterns …