在线内容消费中用户好奇心的分析与建模:以LastFM为例

A. M. Sousa, J. Almeida, F. Figueiredo
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引用次数: 1

摘要

好奇心是人类行为的自然特征。当我们考虑到我们花在网上消费内容上的时间时,我们可以预期,至少有一小部分时间是由好奇行为驱动的。为了理解好奇心是如何驱动在线信息消费的,我们在这里提出了一个基于几个刺激指标来捕捉用户好奇心的模型。我们的模型依赖于心理学中公认的冯特曲线,并基于捕捉新颖性、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。作为一个案例研究,我们将我们的模型应用于LastFM的在线音乐消费数据集。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。这些特点是基于歌曲,艺术家和音乐流派的多样性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analyzing and Modeling User Curiosity in Online Content Consumption: A LastFM Case Study
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.
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