Influencing (and being influenced by) others indirectly through social networks is fundamental to all human societies. Whether this happens through the diffusion of rumors, viruses, opinions, or know-how, finding the source is of persistent interest to people and an algorithmic challenge of much current research interest. However, no study has considered the case of diffusion sources actively trying to avoid detection. By disregarding this assumption, we risk conflating intentional obfuscation from the fundamental limitations of source-finding algorithms. We close this gap by separating two mechanisms hiding diffusion sources-one stemming from the network topology itself and the other from strategic manipulation of the network. We find that identifying the source can be challenging even without foul play and, many times, it is easy to evade source-detection algorithms further. We show that hiding connections that were part of the viral cascade is far more effective than introducing fake individuals. Thus, efforts should focus on exposing concealed ties rather than planted fake entities, e.g., bots in social media; such exposure would drastically improve our chances of detecting the source of a social diffusion.

中文翻译：

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社会扩散源可以逃避检测

通过社会网络间接影响他人（并受到他人影响）对于所有人类社会都是至关重要的。无论是通过散布谣言，病毒，观点还是专有技术来实现，寻找源一直是人们的持久兴趣，也是当前许多研究兴趣所面临的算法挑战。但是，没有研究考虑过积极尝试避免扩散的扩散源。通过忽略此假设，我们有可能将故意混淆与源查找算法的基本限制相混淆。我们通过分离两种隐藏扩散源的机制来弥合这一差距，一种是源于网络拓扑本身，另一种是源于网络的战略操纵。我们发现，即使没有犯规行为，识别来源也可能具有挑战性，而且很多时候，进一步逃避源检测算法很容易。我们表明，隐藏属于病毒级联的连接比引入假人要有效得多。因此，工作应着重于公开隐藏的联系，而不是种植假冒实体，例如社交媒体中的机器人；这种接触将大大提高我们发现社会扩散源的机会。