Pattern Recognition of Dynamic Social Network

Abstract

The continuous transformation of civilization caused the connections between society have become more sufficient and persistent. Interaction between human society have spread widely around the globe due to the swift development of technology and internet. The accumulation of people social interaction forms huge-scale unstructured data which changes over time, called the User Generated Content (UGC). The traditional method for analyzing social interactions, namely Social Network Analysis (SNA), only focuses on static social network properties without seeing changes that occur over time. Social network in the real world can be considered to be dynamic processes because individuals follow and quit social interaction by that transforming network structure. Dynamic Network Analysis (DNA) can analyze dynamic social network through graph over time to view pattern recognition of dynamic social interaction during research period. In this observation, we analyze dynamic social network from social media, precisely in Twitter. Case studies used in this research are online transportation, bank, television channel, and online news portal by reason of they are having immense dynamic interactions in social media. Analysis of dynamic network using graph over time to view the evolution of network properties.