With the growth of online information, varying personalization drifts and volatile behaviors of
internet users, recommender systems are effective tools for information filtering to overcome …

Sentiment analysis is an increasingly evolving field of research in computer science. With
the considerable number of studies on innovative sentiment analysis available, it is worth …

This study explores how using social networking sites (SNSs) to cope with stressors induced
by a global pandemic (in this case, COVID-19) can have negative consequences. The …

The advancement in digital technologies has led to an explosive information phenomenon,
particularly in Internet shopping. This paper attempts to examine the trust element in the …

The goal of a recommender system is to return related items that users may be interested in.
However recommendation methods result in a sparsity problem that affects the generation of …

There has always been a gap between research and engineering practices across almost
all disciplines. The nature of these gaps are not identified; However, in order to be able to …

These days users are able to save their time and effort by purchasing products online via
various e-commerce websites. Their experience with a product exists in the form of textual …

Identification of users' polarities and mining their opinions in various areas, especially social
networks, has become one of the popular and useful research fields. Although opinion …

The development of social media technologies has greatly enhanced social interactions.
The proliferation of social platforms has generated massive amounts of data and a …

Hotel recommender systems are crucial tools that assist tourists in filtering through
extraneous hotel information, ensuring they find accommodations that align with their …