The increasing popularity and diversity of social media sites has encouraged more and
more people to participate on multiple online social networks to enjoy their services. Each …

Consuming news from social media is becoming increasingly popular. Social media
appeals to users due to its fast dissemination of information, low cost, and easy access …

The growth of social media over the last decade has revolutionized the way individuals
interact and industries conduct business. Individuals produce data at an unprecedented rate …

In this paper, we adopt the representation learning approach to align users across multiple
social networks where the social structures of the users are exploited. In particular, we …

Sarcasm is a nuanced form of language in which individuals state the opposite of what is
implied. With this intentional ambiguity, sarcasm detection has always been a challenging …

Predicting anchor links across social networks has important implications to an array of
applications, including cross-network information diffusion and cross-domain …

Sentiment analysis is the computational study of people's opinions, sentiments, emotions,
moods, and attitudes. This fascinating problem offers numerous research challenges, but …

More often than not, people are active in more than one social network. Identifying users
from multiple heterogeneous social networks and integrating the different networks is a …

Multiple networks naturally appear in numerous high-impact applications. Network
alignment (ie, finding the node correspondence across different networks) is often the very …

Multilayer networks, in particular multilayer social networks, where users belong to and
interact on different networks at the same time, are an active research area in social network …