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Dynamics of Online Collective Attention as Hawkes Self-exciting Process
Open Physics ( IF 1.8 ) Pub Date : 2020-01-31 , DOI: 10.1515/phys-2020-0002
Zhenpeng Li 1 , Tang Xijin 2, 3
Affiliation  

Abstract Understanding the dynamic formation mechanism of online collective attention has been attracted diversified interests such as Internet memes, viral videos, or social media platforms and Web-based businesses, and has practical application in the area of marketing and advertising, propagation of information. Bulletin Board System, or BBS can be regarded as an ecosystem of digital resources connected and shaped by collective successive behaviors of users. Clicks and replies of the posts quantify the degree of collective attention. For example, the collective clicking behavior of users on BBS gives rise to the up and down of focus on posts, and transporting attention between topics, the ratio between clicks and replies measure the heat degree of a post. We analyzed the dynamics of collective attention millions of users on an interactive Tianya Zatan BBS. By analyzing the dynamics of clicks we uncovered a non-trivial Hawkes process self-exciting regularity concerning the impact of novelty exponential decay mechanism. Here, it able to explain the empirical data of BBS remarkably well, such as popular topics are observed in time frequently cluster, asymptotic normality of clicks. Our findings indicate that collective attention among large populations decays with a exponential decaying law, suggest the existence of a natural time scale over novelty fades. Importantly, we show that self-exciting point processes can be used for the purpose of collective attention modeling.

中文翻译:

作为霍克斯自激过程的在线集体注意力的动态

摘要 了解在线集体注意力的动态形成机制已经引起了互联网模因、病毒视频或社交媒体平台和基于网络的业务等多种兴趣,并在营销和广告、信息传播等领域具有实际应用。Bulletin Board System,简称BBS,可以看作是一个由用户的集体连续行为连接和塑造的数字资源生态系统。帖子的点击和回复量化了集体关注的程度。例如,用户在 BBS 上的集体点击行为会引起对帖子的关注度的上升和下降,以及主题之间的注意力转移,点击率和回复率衡量帖子的热度。我们在互动的天涯杂谈论坛上分析了数百万用户集体关注的动态。通过分析点击的动态,我们发现了一个非平凡的霍克斯过程自激规律,涉及新奇指数衰减机制的影响。在这里,它能够很好地解释BBS的经验数据,例如热门话题被及时观察到频繁聚类,点击量渐近正态性。我们的研究结果表明,大量人群中的集体注意力以指数衰减规律衰减,这表明存在新奇消失的自然时间尺度。重要的是,我们表明自激点过程可用于集体注意力建模的目的。通过分析点击的动态,我们发现了一个非平凡的霍克斯过程自激规律,涉及新奇指数衰减机制的影响。在这里,它能够很好地解释BBS的经验数据,例如热门话题被及时观察到频繁聚类,点击量渐近正态性。我们的研究结果表明,大量人群中的集体注意力以指数衰减规律衰减,这表明存在新奇消失的自然时间尺度。重要的是,我们表明自激点过程可用于集体注意力建模。通过分析点击的动态,我们发现了一个非平凡的霍克斯过程自激规律,涉及新奇指数衰减机制的影响。在这里,它能够很好地解释BBS的经验数据,例如热门话题被及时观察到频繁聚类,点击量渐近正态性。我们的研究结果表明,大量人群中的集体注意力以指数衰减规律衰减,这表明存在新奇消失的自然时间尺度。重要的是,我们表明自激点过程可用于集体注意力建模的目的。我们的研究结果表明,大量人群中的集体注意力以指数衰减规律衰减,这表明存在新奇消失的自然时间尺度。重要的是,我们表明自激点过程可用于集体注意力建模。我们的研究结果表明,大量人群中的集体注意力以指数衰减规律衰减,这表明存在新奇消失的自然时间尺度。重要的是,我们表明自激点过程可用于集体注意力建模的目的。
更新日期:2020-01-31
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