Outliers are also referred to as abnormalities, discordants, deviants, or anomalies in the data
mining and statistics literature. In most applications, the data is created by one or more …

In this expository article we give an overview of some statistical methods for the monitoring
of social networks. We discuss the advantages and limitations of various methods as well as …

Online social networks play a major role in the spread of information at very large scale. A lot
of effort have been made in order to understand this phenomenon, ranging from popular …

The convergence of multi-disciplinary knowledge may spur emerging technologies. It is
important to understand this convergence process that helps to identify these emergent …

Due to the ever-growing amount of data, computer-aided methods and systems to detect
weak signals and trends for corporate foresight are in increasing demand. To this day, many …

In this paper, we consider learning dictionary models over a network of agents, where each
agent is only in charge of a portion of the dictionary elements. This formulation is relevant in …

As global digitization continues to grow, technology becomes more affordable and easier to
use, and social media platforms thrive, becoming the new means of spreading information …

Online social media are increasingly facilitating our social interactions, thereby making
available a massive “digital fossil” of human behavior. Discovering and quantifying distinct …

Product features can be classified into different categories based on customer opinions. The
rapid development of artificial intelligence and machine learning paves the way toward …

The emergence and popularization of online social networks suddenly made available a
large amount of data from social organization, interaction and human behavior. All this …