Social Media K-H Networks are novel network models that recently emerged as Social Media exploded in popularity. The networks are based on relations between keywords and hashtags that can be computed by various means of computational algorithms. The current model is merely based on the associations that are derived by means of (Apriori, FPGrowth) algorithms. Such networks have proven to be promising when explored via means of network mining algorithms (such as HashnetMiner). K-H Networks have also demonstrated the phenomenon of a shrinking world, which shed light on the structure and the type of the network which can be linked to Small-World Networks. We hope to advance the science of network analysis and mining by offering this workshop which we believe will encourage further exploration in K-H Networks structure and mining.

The objective of this workshop is to advance the current knowledge of K-H Networks scope from various point of view: (1) Expanding the scope of the K-H Networks beyond associations and explore other type of relations (e.g., causality, proximity, n-grams, semantics). (2) Understanding the structure of the networks using Big Data sets. (3) Exploring the network structural properties. (4) Designing new network mining algorithms for Big Data networks. (5) Exploring the networks in various application domain (e.g., climate change, environmental sciences, business, biological sciences, biomedical sciences, and political polarization)

The manuscript should follow IEEE Computer Society's two-column format. The maximum manuscript length is eight (8) pages including tables, figures, and references. Accepted papers are published by IEEE Computer Society in ASONAM 2015 official proceedings.