什么是手机通话邓巴数？

Facebook和YouTube用户的极化是什么？

城市拥堵和什么因素有关？

集智复杂文摘翻译小组为你呈现新鲜的研究内容！

手机通话的邓巴数（Calling Dunbar’s Numbers）

April 14, 5:40 PM

BY Pádraig MacCarron, Kimmo Kaski, Robin Dunbar

(Translated by – 卢罡)

(Edited by 唐璐)

社会脑假说预测，在任何时候，人类平均能够维系大约150个人际关系。在这150个人际关系中，存在分层次的朋友关系，层次的情感亲密度越低，该层次中朋友的数量越多。我们分析了一个移动电话通话数据集，首先确定是否能够根据通话频度分辨出朋友层次。然后，我们应用了不同的聚类算法，将个体的通话频次分成多个簇，并将每个簇的大小与社会脑假说所预测的层次大小进行比较。在这个数据集中，我们发现了层次结构存在的强有力证据。聚类产生的结果在最内和最外层次上与前人的研究结果高度吻合，但是我们观察到，中间那些层次的变化很大。

The social brain hypothesis predicts that humans have an average of about 150 relationships at any given time. Within this 150, there are layers of friends of an ego, where the number of friends in a layer increases as the emotional closeness decreases. Here we analyse a mobile phone dataset, firstly, to ascertain whether layers of friends can be identified based on call frequency. We then apply different clustering algorithms to break the call frequency of egos into clusters and compare the number of alters in each cluster with the layer size predicted by the social brain hypothesis. In this dataset we find strong evidence for the existence of a layered structure. The clustering yields results that match well with previous studies for the innermost and outermost layers, but for layers in between we observe large variability.

原文链接：http://arxiv.org/abs/1604.02400

Facebook和YouTube用户的极化

（Users Polarization on Facebook and Youtube）

April 13, 11:18 PM

BY Alessandro Bessi, Fabiana Zollo, Michela Del Vicario, Michelangelo Puliga, Antonio Scala, Guido Caldarelli, Brian Uzzi, Walter Quattrociocchi

(Translated by – dan)

(Edited by 唐璐)

根据用户偏好的内容推介算法可能屏蔽偏好范围以外的内容。我们在1200万用户样本上研究了相同内容（视频）在不同平台上（例如，Facebook和YouTube）是如何被阅读的。我们发现，相同的内容就能导致形成回声室效应，与在线社交网络无关，因此也与内容推介算法无关。最后，我们发现，用户的评论模式能够提早准确地预测回声室的形成。

Algorithms for content promotion accounting for users preferences, might limit the exposure to unsolicited contents. In this work, we study how the same contents (videos) are consumed on different platforms — i.e. Facebook and YouTube — over a sample of 12M of users. Our findings show that the same content lead to the formation of echo chambers, irrespective of the online social network and thus of the algorithm for content promotion. Finally, we show that the users’ commenting patterns are accurate early predictors for the formation of echo-chambers.

原文链接：http://arxiv.org/abs/1604.02705

城市地区拥堵的全球分析

（ A global take on congestion in urban areas）

April 14, 3:38 PM BY Marc Barthelemy

(Translated by -余思瑶)

(Edited by 唐璐)

我们分析了由一家GPS设备公司（TomTom）收集的全世界大约300个城市地区的拥堵数据。使用简单的缩放参数和数据拟合，我们发现，大城市中高峰时段的拥堵基本是随人口密度的平方根增长。这个结果，与之前出版物所显示的汽油消耗量随密度增加而减少的观点相悖，证实了人口密度确实是拥堵的一个重要的决定因素，我们也急需对这个现象有更好的理论认识。在城市层面上进行的分析的不完善，让我们意识到只考虑人口密度本身对于拥堵研究很有误导性，关注活动和居住的空间分布可能更有用。

We analyze the congestion data collected by a GPS device company (TomTom) for almost 300 urban areas in the world. Using simple scaling arguments and data fitting we show that congestion during peak hours in large cities grows essentially as the square root of the population density. This result, at odds with previous publications showing that gasoline consumption decreases with density, confirms that density is indeed an important determinant of congestion, but also that we need urgently a better theoretical understanding of this phenomena. This incomplete view at the urban level leads thus to the idea that thinking about density by itself could be very misleading in congestion studies, and that it is probably more useful to focus on the spatial redistribution of activities and residences.