by Tang et al. (tang2009), SIGKDD
Tang et al. (2009) propose Topical Affinity Propagation (TAP) for determining the topic-level social influence of nodes in large networks. They introduce a distributed learning algorithm based on map reduce to compute influence graphs using TAP for identifying
- the most representative nodes for a given topic
- the influence of neighbor nodes on a particular node
- ways to quickly connect to a particular node through strong social ties
- multi-aspect: nodes can have different influence on each other depending on the topic
- link-specific importance (weight) between nodes rather than fixed node importance values.