Learning to rank has been intensively studied and widely applied in information retrieval.
Typically, a global ranking function is learned from a set of labeled data, which can achieve …

In recent years, online social networking has revolutionized interpersonal communication.
The newer research on language analysis in social media has been increasingly focusing …

Ranking is a core task in recommender systems, which aims at providing an ordered list of
items to users. Typically, a ranking function is learned from the labeled dataset to optimize …

Twitter has evolved from being a conversation or opinion sharing medium among friends
into a platform to share and disseminate information about current events. Events in the real …

We study an interesting phenomenon of social influence locality in a large microblogging
network, which suggests that users' behaviors are mainly influenced by close friends in their …

This article investigates the effect of video loggers (vloggers) popularity on consumer
credibility perception and purchase intention. It employs a two (high versus low vlogger …

In learning-to-rank for information retrieval, a ranking model is automatically learned from
the data and then utilized to rank the sets of retrieved documents. Therefore, an ideal …

Twitter has rapidly grown to a popular social network in recent years and provides a large
number of real-time messages for users. Tweets are presented in chronological order and …

Social influence occurs when one's opinions, emotions, or behaviors are affected by others
in a social network. However, social influence takes many forms, and its underlying …

Users of popular services like Twitter and Facebook are often simultaneously overwhelmed
with the amount of information delivered via their social connections and miss out on much …