一种研究论坛动态的时间解耦方法
A Time Decoupling Approach for Studying Forum Dynamics
摘要：
在线论坛是关于用户通信活动的丰富信息来源。在在线论坛的交流线索中发现时间模式可以促进我们对对话动态的理解。在这种情况下，时间分析的主要挑战是论坛数据的复杂性。可以有成千上万的交互用户，他们可以用许多不同的方式进行数字描述。此外，用户特征可以随着时间的推移而演变。我们提出了一种方法，将用户的时间信息转换为用户事件和事件间时间的序列。我们开发了一个新的特征空间来表示路径的事件序列，我们模型的事件间的时间分布。我们研究了四个互联网论坛的30，000多名用户，发现了用户交流的新模式。我们发现，随着时间的推移，用户倾向于表现出一致性。此外，在我们的特征空间中，我们观察到代表不太可能的用户行为的区域。最后，我们将展示如何为每个论坛导出一个数值表示，然后使用此表示导出多个论坛的新聚类。
英文摘要：
Online forums are rich sources of information about user communication activity over time. Finding temporal patterns in online forum communication threads can advance our understanding of the dynamics of conversations. The main challenge of temporal analysis in this context is the complexity of forum data. There can be thousands of interacting users, who can be numerically described in many different ways. Moreover, user characteristics can evolve over time. We propose an approach that decouples temporal information about users into sequences of user events and inter-event times. We develop a new feature space to represent the event sequences as paths, and we model the distribution of the inter-event times. We study over 30,000 users across four Internet forums, and discover novel patterns in user communication. We find that users tend to exhibit consistency over time. Furthermore, in our feature space, we observe regions that represent unlikely user behaviors. Finally, we show how to derive a numerical representation for each forum, and we then use this representation to derive a novel clustering of multiple forums.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
