误传
计算机科学
社会化媒体
互联网隐私
病毒式营销
社交网络(社会语言学)
谣言
遏制(计算机编程)
计算机安全
数据科学
万维网
政治学
公共关系
程序设计语言
作者
Nam P. Nguyen,Guanhua Yan,My T. Thai,Stephan Eidenbenz
标识
DOI:10.1145/2380718.2380746
摘要
With their blistering expansions in recent years, popular on-line social sites such as Twitter, Facebook and Bebo, have become some of the major news sources as well as the most effective channels for viral marketing nowadays. However, alongside these promising features comes the threat of misinformation propagation which can lead to undesirable effects, such as the widespread panic in the general public due to faulty swine flu tweets on Twitter in 2009. Due to the huge magnitude of online social network (OSN) users and the highly clustered structures commonly observed in these kinds of networks, it poses a substantial challenge to efficiently contain viral spread of misinformation in large-scale social networks.
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