These days, many recommender systems (RS) are utilized for solving information overload
problem in areas such as e-commerce, entertainment, and social media. Although classical …

Researchers have collected Twitter data to study a wide range of topics. This growing body
of literature, however, has not yet been reviewed systematically to synthesize Twitter-related …

Twitter is the third most popular worldwide Online Social Network (OSN) after Facebook and
Instagram. Compared to other OSNs, it has a simple data model and a straightforward data …

Abstract Information technology has spread widely, and extraordinarily large amounts of
data have been made accessible to users, which has made it challenging to select data that …

Recommender systems suggest items that users might like according to their explicit and
implicit feedback information, such as ratings, reviews, and clicks. However, most …

Recommender systems attempt to provide effective suggestions to each user based on their
interests and behaviors. These recommendations usually match the personal user …

Social applications foster the involvement of end users in Web content creation, as a result
of which a new source of vast amounts of data about users and their likes and dislikes has …

Social recommender systems have transformed how consumers seek product-or service-
related information. Based on Bagozzi's self-regulation framework, this study examines the …

Context-aware recommender systems dedicated to online social networks experienced
noticeable growth in the last few years. This has led to more research being done in this …

The increasing amount of marketing content in e-commerce websites results in the limited
attention of users. For recommender systems, the way recommended items are presented …