社交媒体作为一种创新——以Twitter为例

Andrew Whinston, Huaxia Rui
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引用次数: 8

摘要

Twitter和YouTube等社交媒体服务为普通人提供了前所未有的机会,让他们可以访问大量内容,并向全球观众发布自己的内容。然而,这些服务的关键创新不在于技术,而在于识别和连接人们对信息和关注的需求。为了更好地理解这一点,我们将社交媒体环境建模为一种经济,其中内容的消费意味着注意力的供应,而注意力的消费是通过内容的供应来实现的。内容的供应和注意力的供应都需要投入时间,因此在这种经济中,时间就是金钱。我们表明,随着这个经济体中人口的增长,存在内容生产的注意力工资,并且人口的分割是整齐的特征。令人惊讶的是,如果用户的效用函数满足一定的线性条件,并且人口规模足够大,那么用户将以概率1的方式自我选择进入内容生产者群体或内容消费者群体,从而形成完美的分工。而且,这种分配均衡的宏观层面的内容消费和生产是稳定的,表明了社交媒体的可持续性。基于我们的模型和从Twitter上收集的大量数据,我们提出并检验了四个假设,统计结果有力地支持了我们的理论。本文对Twitter和YouTube等近期社交媒体服务的独特创新提供了重要见解。它也为许多大型社交媒体网站上的搭便车现象提供了一个新的视角。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Social Media as an Innovation - The Case of Twitter
Social media services such as Twitter and YouTube are offering unprecedented opportunities for ordinary people to access a huge amount of content and to publish their own content for a global audience. The key innovation of these services, however, is not technological, rather, it's about recognizing and connecting people's need for information and attention. To better understand this, we model a social media environment as an economy where consumption of content means supply of attention and consumption of attention is through supply of content. Both the supply of content and the supply of attention involve investment of time, hence time is money in this economy. We show that as the population in this economy grows large, there exists an attention wage for content production and the segmentation of the population is neatly characterized. Surprisingly, if users' utility functions satisfy a certain linearity condition and the population size is large enough, then with probability 1, users will self-select into either the group of content producers or the group of content consumers, resulting in a perfect division of labor. Moreover, the macro-level content consumption and production of such partition equilibrium is stable, suggesting the sustainability of the social media.Based on our model and a massive collection of data from Twitter, we propose and test four hypotheses, and the statistical results give strong support to our theory. This paper gives important insights into the unique innovation of recent social media services like Twitter and YouTube. It also provides a new perspective on the free-riding phenomenon in many large social media sites.
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