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Analyzing and Modeling User Curiosity in Online Content Consumption: A LastFM Case Study

机译:在线内容消费中用户好奇心的分析和建模:LastFM案例研究

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Curiosity is a natural trait of human behavior. When we take into account the time we spend consuming content online, it is expected that at least a fraction of that time was driven by curious behavior. Aiming at understanding how curiosity drives online information consumption, we here propose a model that captures user curiosity relying on several stimulus metrics. Our model relies on the well-established Wundt's curve from psychology and is based on metrics capturing Novelty, Complexity and Uncertainty as key stimuli driving one's curiosity. As a case study, we apply our model on a dataset of online music consumption from LastFM. We found that there are four main types of user behaviors in terms of how the curiosity stimulus metrics drive the user accesses to online music. These are characterized based on the diversity in the songs, artists and musical genres accessed.
机译:好奇心是人类行为的自然特征。考虑到我们在网上消费内容所花费的时间,预计至少有一部分时间是由好奇的行为所驱动。为了理解好奇心如何驱动在线信息消费,我们在这里提出一种模型,该模型依赖于多种刺激指标来捕获用户的好奇心。我们的模型基于心理学上公认的Wundt曲线,并基于捕获新颖性,复杂性和不确定性作为驱动人们好奇心的关键刺激的指标。作为案例研究,我们将模型应用于LastFM在线音乐消费的数据集。我们发现,就好奇心刺激指标如何驱动用户访问在线音乐而言,用户行为主要有四种类型。这些特征基于所访问的歌曲,艺术家和音乐流派的多样性而定。

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