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 …

Computing subgraph frequencies is a fundamental task that lies at the core of several
network analysis methodologies, such as network motifs and graphlet-based metrics, which …

Graph mining, which finds specific patterns in the graph, is becoming increasingly important
in various domains. We point out that accelerating graph mining suffers from the following …

Computation on sparse data is becoming increasingly important for many applications.
Recent sparse computation accelerators are designed for specific algorithm/application …

Network motif is a kind of frequently occurring subgraph that reflects local topology in
graphs. Although network motif has been studied in graph analytics, eg, social network and …

Graph pattern mining applications try to find all embeddings that match specific patterns.
Compared to the traditional graph computation, graph mining applications are computation …

Graph pattern mining (GPM) is an important application that identifies structures from
graphs. Despite the recent progress, the performance gap between the state-of-the-art GPM …

Motivation Scientists increasingly rely on intelligent information systems to help them in their
daily tasks, in particular for managing research objects, like publications or datasets. The …

Complex networks facilitate the understanding of natural and man-made processes and are
classified based on the concepts they model: biological, technological, social or semantic …

Social bots are software programs that automatically produce messages and interact with
human users on social media platforms. In this paper, we provide an analysis of the emotion …