人肉搜索中社会影响与协同影响的比较

Saran Chen, Tao Wang, Yanzhe Feng, Zhong Liu, Jincai Huang
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摘要

以往的研究认为,具有较大社会影响力的个体在协作活动中起着重要的作用。然而,在源自中国网络社交网络的典型协同活动——人肉搜索(Human Flesh Search, HFS)中,我们并没有得到相同的结论,而是发现社会影响力与协同影响力之间的相关性较弱。具体而言,我们首先从爬虫数据中构建HFS参与者的社会网络和协作网络两个网络,并分别量化社会影响和协作影响。然后,我们计算了社会影响和协作影响之间的相关关系。在此基础上,利用BIC测度和k- meme++聚类算法得到了三种不同类型的参与者,并计算了不同类型参与者之间社会影响力和协作影响力的相关性。虽然不同类型之间存在差异,但所有结果都表明社会影响与协作影响之间的相关性较弱。
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Comparing Social Influence with Collaborative Influence in Human Flesh Search
Previous studies believe that the individuals who have great social influence play an important role in the collaborative activity. However, in Human Flesh Search (HFS), which is a typical collaborative activity originated from Chinese online social networks, we do not obtain the same conclusion but find that the correlation between social influence and collaborative influence is weak. Specifically, we first construct two networks from the crawling data, i.e., the social network and collaborative network of HFS participants, and quantify social influence and collaborative influence separately. Then we calculate the correlation between social influence and collaborative influence. Furthermore, we obtain three different types of participants by using BIC measure and k-means++ clustering algorithm and calculate the correlation between social influence and collaborative influence among different types. Although there exist differences in different types, all the results show that the correlation between social influence and collaborative influence is weak.
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