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Live on TV, Alive on Twitter: Quantifying Continuous Partial Attention of Viewers During Live Television Telecasts

机译:在电视上直播,在Twitter上直播:量化直播电视广播期间观众的部分连续关注

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Even while engaged in an attention-consuming activity such as watching TV, social media users often end up paying attention to one or more social media. This is an example of a behavioral phenomenon called Continuous Partial Attention (CPA). Quantification of user attention can be a valuable metric in understanding user behavior under scenarios where their attention is divided. In this study, we propose a generalized model to quantify CPA given a primary and a secondary task, also knows as a distraction. Given a history of distractions, we compute a temporal attention profile for a user while incorporating a penalty for continual distraction. We analyze the model using the scenario of TV viewers who tweeted while watching the ten episodes of the sixth season of the popular TV show 'Game of Thrones' (GoT). We calculate attention profiles and CPA of 438 prolific users who tweeted during each episode of the show. Using this metric, we classify these users into Attentive and Partially Attentive viewers. We compare users from both classes in terms of their attention profiles. We also compare their tweeting behavior during live telecast of GoT to their normal tweeting behavior. We examine CPA across users during an episode vis-a-vis important events in the episode. We find that the CPA metric captures the effects of volume and lengths of the tweets, as well as their temporal distribution.
机译:即使在进行诸如观看电视之类的耗费精力的活动时,社交媒体用户也常常最终会注意一种或多种社交媒体。这是一种行为现象的示例,称为连续局部注意力(CPA)。量化用户注意力是了解用户注意力分散情况下用户行为的重要指标。在这项研究中,我们提出了一个通用模型来量化CPA,这既定了主要任务和次要任务,也被称为分散注意力。给定分心的历史,我们在为用户计算时间注意力分布的同时合并持续分心的惩罚。我们使用电视观众在观看流行电视节目《权力的游戏》(GoT)第六季的十集时发推文的场景来分析模型。我们计算了在节目的每一集中发推文的438位多产用户的注意力概况和CPA。使用此指标,我们将这些用户分为“专心”和“部分专心”查看器。我们根据他们的注意力概况比较了这两个班级的用户。我们还将GoT直播期间他们的推文行为与正常的推文行为进行了比较。我们针对某个事件中的重要事件比较了一个事件中各个用户的每次转化费用。我们发现,CPA指标可以捕获推文的音量和长度以及其时间分布的影响。

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