Much research effort has been conducted to analyze information of social networks, such as finding the influential users. Our aim is to identify the most influential users based on their interactions in posting on a given topic. We first proposes a graph model of online posts, which represents the relationships between online posts of one topic, so as to find the influential posts on the topic. Based on the influential posts found, the post graph is transformed to a user graph that can be used to discover influential users with improved influence measures. Finally the most influential users can be determined by considering the properties and measures from both graphs. In our work, two types of influences are defined based on two roles: starter and connecter. A starter is followed by many others, similar to a hub in a network; while a connecter is to help bridging two different starters and their corresponding clusters. In this paper, different measures on the graphs are introduced to calculate the influences on the two roles.
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||3rd International Workshops on Modeling Social Media, MSM 2012|
|Period||25/06/12 → 25/06/12|
- Theoretical Computer Science
- Computer Science(all)