Recommender Systems (RS) are established to deal with the preferences of users to
enhance their experience and interest in innumerable online applications by streamlining …

The way we talk carries information about who we are. Demographics, personality, clinical
conditions, political preferences influence what we speak about and how, suggesting that …

People come to social media to satisfy a variety of needs, such as being informed,
entertained and inspired, or connected to their friends and community. Hence, to design a …

This paper presents an innovative approach to address the problems researchers face in
Emotion Aware Recommender Systems (EARS): the difficulty and cumbersome collecting …

A social network is a decent platform in which users share daily emotions and opinions. As a
consequence, they have become an essential information source related to …

We derive a method to enhance the evaluation for a text-based Emotion Aware
Recommender that we have developed. However, we did not implement a suitable way to …

Automatic emotion recognition is a hot topic with a wide range of applications. Much work
has been done in the area of automatic emotion recognition in recent years. The focus has …

In this paper, a novel re-engineering mechanism for the generation of word embeddings is
proposed for document-level sentiment analysis. Current approaches to sentiment analysis …

Emotion, intricately woven through the brain's structures, involves complex neural processes
in the brain stem, amygdala, insula, and anterior cingulate cortex. This intentional and …

This paper utilizes an ingenious text-based affective aware pseudo association method
(AAPAM) to link disjoint users and items across different information domains and leverage …