发表机构
University of Colorado Colorado Springs; United States Air Force Academy（科罗拉多大学科罗拉多斯普林斯分校; 美国空军学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出TH-EE框架，通过区分持续性、近因性和再涌现三个维度，更准确地刻画在线关注度的时间剖面，并在YouTube和维基百科数据上验证其有效性。
AI 中文摘要
在线关注度通常使用累计量、峰值活动或算术平均值来概括，但此类度量可能掩盖随时间持续的活动、集中在近期的活动或休眠后重新出现的活动之间的差异。本文引入了时间视野参与有效性（TH-EE）框架，该框架通过区分三个相关但不等价的属性来构建在线关注度的可解释时间剖面：持续性、近因性和再涌现。我们通过受控参与轨迹、对37个主题中1,850个YouTube视频的概念验证应用（其中18个队列先验地选为持续性、急性、周期性和近期起源关注的范例，19个队列对应于权威性辟谣的说法），以及对相同主题的十一年每日维基百科页面浏览量序列进行事件级验证来评估该框架。受控分析表明，该框架能区分分布式活动与集中式爆发，通过近因性加权引入时间顺序敏感性，并识别在定义的休眠间隔后的重新活动。在事件级序列上，该框架的重新激活与Kleinberg爆发起始点和PELT变点共现的频率远高于偶然情况。YouTube应用表明，辟谣说法队列并未占据时间剖面空间的独特区域；它们表现出与良性主题大幅重叠的异质模式。这些结果支持将持续性、近因性和再涌现视为在线关注度的独立维度。TH-EE是一个描述性和比较性的测量框架，而非错误信息、协调、意图或内容真实性的分类器。
英文摘要
Online attention is commonly summarized using cumulative volume, peak activity, or arithmetic averages, but such measures can obscure differences between activity that is sustained over time, concentrated near the present, or renewed after dormancy. This paper introduces the Time-Horizon Engagement Effectiveness (TH-EE) framework, which constructs interpretable temporal profiles of online attention by distinguishing three related but non-equivalent properties: persistence, recency, and re-emergence. We evaluate the framework through controlled engagement traces, a proof-of-concept application to 1,850 YouTube videos across 37 topics (18 cohorts selected a priori as exemplars of persistent, acute, cyclical, and recently originating attention, and 19 cohorts corresponding to authoritatively debunked claims), and an event-level validation on eleven years of daily Wikipedia pageview series for the same topics. The controlled analyses show that the framework distinguishes distributed activity from concentrated bursts, introduces temporal-order sensitivity through recency weighting, and identifies renewed activity after a defined dormant interval. On the event-level series, the framework's reactivations co-locate with Kleinberg burst onsets, and PELT change points far more often than chance. The YouTube application shows that debunked-claim cohorts do not occupy a unique region of temporal-profile space; they exhibit heterogeneous patterns that overlap substantially with benign topics. These results support treating persistence, recency, and re-emergence as separate dimensions of online attention. TH-EE is a descriptive and comparative measurement framework, not a classifier of misinformation, coordination, intent, or content veracity.
