An Improvised Model for Identifying Influential Nodes in Multi-parameter Social Networks
نویسندگان
چکیده
Influence Maximization is one of the major tasks in the field of viral marketing and community detection. Based on the observation that social networks in general are multi-parameter graphs and viral marketing or Influence Maximization is based on few parameters, we propose to convert the general social networks into “interest graphs”. We have proposed an improvised model for identifying influential nodes in multi-parameter social networks using these “interest graphs”. The experiments conducted on these interest graphs have shown better results than the method proposed in [8].
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