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Ranking of Influential users based on User-Tweet bipartite graph

机译:基于User-Tweet两分图的有影响力的用户排名

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Today, even if we are still geographically situated, but real-time news and trends are able to reach us no matter how far we are or how huge is the time difference. This is due to Social Networks Services and the strong involvement of people to them through posting, sharing and interacting online with information. Therefore, we propose a study on patterns of information diffusion on Twitter during global scale events. We also introduce a method for identifying influencers and quantify popularity of Tweets on the Network based on a user-tweet bipartite graph.
机译:今天,即使我们仍然位于地理位置,而且实时新闻和趋势无论我们多远或多么巨大,都可以实现我们的趋势。这是由于社交网络服务和人们通过发布,共享和交互与信息互动的强烈参与。因此,我们建议研究全球规模事件期间推特上的信息扩散模式。我们还介绍了一种用于识别影响者的方法,并根据用户推文二分图来识别网络上推文的普及。

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