Department of Theoretical Physics, JoŽef Stefan Institute, Ljubljana, Slovenia.
J R Soc Interface. 2013 Feb;10(79):20120819. doi: 10.1098/rsif.2012.0819.
Quantitative study of collective dynamics in online social networks is a new challenge based on the abundance of empirical data. Conclusions, however, may depend on factors such as user's psychology profiles and their reasons to use the online contacts. In this study, we have compiled and analysed two datasets from MySpace. The data contain networked dialogues occurring within a specified time depth, high temporal resolution and texts of messages, in which the emotion valence is assessed by using the SentiStrength classifier. Performing a comprehensive analysis, we obtain three groups of results: dynamic topology of the dialogues-based networks have a characteristic structure with Zipf's distribution of communities, low link reciprocity and disassortative correlations. Overlaps supporting 'weak-ties' hypothesis are found to follow the laws recently conjectured for online games. Long-range temporal correlations and persistent fluctuations occur in the time series of messages carrying positive (negative) emotion; patterns of user communications have dominant positive emotion (attractiveness) and strong impact of circadian cycles and interactivity times longer than 1 day. Taken together, these results give a new insight into the functioning of online social networks and unveil the importance of the amount of information and emotion that is communicated along the social links. All data used in this study are fully anonymized.
基于丰富的实证数据,对在线社交网络中的集体动态进行定量研究是一个新的挑战。然而,结论可能取决于用户的心理特征及其使用在线联系人的原因等因素。在这项研究中,我们从 MySpace 上编译和分析了两个数据集。这些数据包含在特定时间深度内发生的网络对话、高时间分辨率和消息文本,其中使用 SentiStrength 分类器评估情绪效价。进行全面分析后,我们获得了三组结果:基于对话的网络动态拓扑结构具有社区的 Zipf 分布、低链接互惠性和非 assortativity 相关性等特征。支持“弱关系”假设的重叠被发现遵循最近为在线游戏提出的规律。携带正(负)情绪的消息时间序列中存在长程时间相关性和持久波动;用户通信模式具有主导的正情绪(吸引力),并且受到昼夜节律和交互性的影响超过 1 天。总之,这些结果为在线社交网络的功能提供了新的见解,并揭示了沿着社交链接传递的信息量和情绪的重要性。本研究中使用的所有数据均经过充分匿名化处理。