In this article, we perform a large-scale study of the Twitter follower network, involving around 0.42 million users who justify DA, to characterize the spreading of DA tweets across the network. Our observations reveal the existence of a very large giant component involving 99% of these users with dense local connectivity that facilitates the spreading of such messages. We further identify active cascades over the network and observe that the cascades of DA tweets get spread over a long distance through the engagement of several closely connected groups of users. Moreover, our observations also reveal a collective phenomenon, involving a large set of active fringe nodes (with a small number of follower and following) along with a small set of well-connected nonfringe nodes that work together toward such spread, thus potentially complicating the process of arresting such cascades. Furthermore, we discovered that the engagement of the users with respect to certain drugs, such as Vicodin, Percocet, and OxyContin, that were observed to be most mentioned in Twitter is instantaneous. On the other hand, for drugs, such as Lortab, that found lesser mentions, the engagement probability becomes high with increasing exposure to such tweets, thereby indicating that drug abusers engaged on Twitter remain vulnerable to adopting newer drugs, aggravating the problem further.

中文翻译：

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Twitter追随者网络的大规模研究，以表征处方药滥用鸣叫的传播

在本文中，我们对Twitter追随者网络进行了大规模研究，其中约有42万用户为DA辩护，以表征DA推文在整个网络中的传播。我们的观察结果表明，存在一个非常庞大的巨型组件，其中99％的用户具有密集的本地连接性，从而促进了此类消息的传播。我们进一步确定了网络上的活动级联，并观察到DA推文的级联通过几个紧密联系的用户组的参与而散布在很长的距离上。此外，我们的观察结果还揭示了一种集体现象，涉及大量活动边缘节点（具有少量跟随者和跟随者）以及一小组相互连接的，良好连接的非边缘节点，它们共同朝着这种传播方向发展，因此潜在地使阻止这种级联反应的过程复杂化。此外，我们发现用户在某些药物（例如Vicodin，Percocet和OxyContin）方面的参与是即时的，这是即时的。另一方面，对于被较少提及的毒品（例如Lortab），随着此类推文的曝光率增加，参与概率也变高，从而表明Twitter上的吸毒者仍然很容易采用新药，从而使问题进一步恶化。