Networks and emotion-driven user communities at popular blogs |
| |
Authors: | M?Mitrovi? G?Paltoglou B?Tadi? |
| |
Institution: | 1.Department of theoretical physics,Jo?ef Stefan Institute,Ljubljana,Slovenia;2.Statistical Cybernetics Research Group, School of Computing and Information Technology University of Wolverhampton,Wolverhampton,UK |
| |
Abstract: | Online communications at web portals represents technology-mediated user interactions, leading to massive data and potentially
new techno-social phenomena not seen in real social mixing. Apart from being dynamically driven, the user interactions via
posts is indirect, suggesting the importance of the contents of the posted material.
We present a systematic way to study Blog data by combined approaches of physics of complex networks and computer science
methods of text analysis. We are mapping the Blog data onto a bipartite network where users and posts with comments are two
natural partitions. With the machine learning methods we classify the texts of posts and comments for their emotional contents
as positive or negative, or otherwise objective (neutral). Using the spectral methods of weighted bipartite graphs, we identify
topological communities featuring the users clustered around certain popular posts, and underly the role of emotional contents
in the emergence and evolution of these
communities. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|