超越沟通强度来估计社交网络中的联系强度
Going beyond communication intensity for estimating tie strengths in social networks
摘要：
尽管关系强度的概念是社会网络分析的核心，但很难量化社会关系的强度。在数据驱动的研究中，估计联系强度的一种典型方法是简单地计算两个人之间接触的总数或持续时间。然而，这忽略了可以从用于社交网络重建的丰富数据集中提取的许多特征。在这里，我们专注于时间信息的联系人数据。我们系统地研究了接触时间序列的特征如何与通常与领带强度相关的拓扑特征相关。我们分析了一个大型的移动电话数据集，并测量了每个领带的通话时间序列的一些属性，并使用这些来预测所谓的邻域重叠，这是一个与社会学文献中的强联系相关的特征。我们观察到时间特征和邻域重叠之间的密切关系，许多特征优于简单的接触计数。突出的特征包括呼叫的天数、突发级联的数量、典型的联系次数和时间稳定性。我们的研究结果表明，这些措施可以适用于社会网络建设，并表明，最好的结果可以通过结合多种时间特征。
英文摘要：
Even though the concept of tie strength is central in social network analysis, it is difficult to quantify how strong social ties are. One typical way of estimating tie strength in data-driven studies has been to simply count the total number or duration of contacts between two people. This, however, disregards many features that can be extracted from the rich data sets used for social network reconstruction. Here, we focus on contact data with temporal information. We systematically study how features of the contact time series are related to topological features usually associated with tie strength. We analyze a large mobile-phone dataset and measure a number of properties of the call time series for each tie, and use these to predict the so-called neighbourhood overlap, a feature related to strong ties in the sociological literature. We observe a strong relationship between temporal features and the neighbourhood overlap, with many features outperforming simple contact counts. Features that stand out include the number of days with calls, number of bursty cascades, typical times of contacts, and temporal stability. Our results suggest that these measures could be adapted for use in social network construction and indicate that the best results can be achieved by combining multiple temporal features.
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