Graph drawing by force-directed placement
Software—Practice & Experience
Information diffusion through blogspace
Proceedings of the 13th international conference on World Wide Web
Tracking Information Epidemics in Blogspace
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
The political blogosphere and the 2004 U.S. election: divided they blog
Proceedings of the 3rd international workshop on Link discovery
GiveALink: mining a semantic network of bookmarks for web search and recommendation
Proceedings of the 3rd international workshop on Link discovery
Efficient top-k querying over social-tagging networks
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
The structure of information pathways in a social communication network
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient overlap and content reuse detection in blogs and online news articles
Proceedings of the 18th international conference on World wide web
A measurement-driven analysis of information propagation in the flickr social network
Proceedings of the 18th international conference on World wide web
Inferring networks of diffusion and influence
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Editorial: Special issue on advances in web intelligence
Neurocomputing
Expert Systems with Applications: An International Journal
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A novel method is presented to analyze the dynamics of social media, i.e., information diffusion properties, for information recommendation and ranking. In social media such as blogs, various information diffuses over time. As a result, a network structure is constructed. In an information diffusion network, each influential information source has an affected subnetwork whose nodes are reachable from it. We define three information diffusion properties of the subnetwork using the numbers of three types of directed two-edge connected subgraphs, which are basic structures in a directed acyclic graph such as an information diffusion network. Each basic structure type is related to information scattering, information gathering, or information transmission. We visualized and analyzed the structure of information diffusion networks extracted for various topics. Furthermore, we characterized the information diffusion properties by using the rank correlation coefficient, precision, and mean reciprocal rank and mean average precision of three types of information sources: official sites, news articles, and consumer generated media pages. We found that the three information diffusion properties have different characteristics and give priority to different types of information sources.