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Co-Orientation of Media Use: Studying Selection and Influence Processes in Social Networks to Link Micro Behavior of TV and YouTube Use to Meso-Level Structures
Communication Methods and Measures ( IF 6.3 ) Pub Date : 2020-04-19 , DOI: 10.1080/19312458.2020.1745766
Thomas N. Friemel 1
Affiliation  

ABSTRACT

Social interactions regarding media content are omnipresent and highlight that media use is closely linked to social life. However, surprisingly little is known about the related social dynamics and their consequences for media use and social relations. This study addresses this topic based on co-orientation theory and investigates the social dynamics of TV and YouTube use among adolescents. A three-wave panel survey among 336 pupils enables us to disentangle which effect the friendship network has on individual media use (RQ1) and which effect media use has on the development and maintenance of friendship ties (RQ2). Based on a multi-level approach of dynamic social network analysis and applying stochastic actor-oriented modeling, we find empirical evidence for processes of social influence regarding TV programs and YouTube channels. No support is found for the hypothesized social selection processes. Along with these empirical insights, the research design demonstrates how the micro-level of individual behavior can be linked with the meso-level of social groups. Furthermore, the insights can be used as a basis to understand larger-scale phenomena emerging on the macro-level of societies and media markets such as audience fragmentation and long-tail audience distributions across media contents.



中文翻译:

媒体使用的协同:研究社交网络中的选择和影响过程,将电视和 YouTube 使用的微观行为与中级结构联系起来

摘要

关于媒体内容的社交互动无处不在,并强调媒体使用与社交生活密切相关。然而,令人惊讶的是,人们对相关的社会动态及其对媒体使用和社会关系的影响知之甚少。本研究基于共同取向理论解决了这一主题,并调查了青少年使用电视和 YouTube 的社会动态。在 336 名学生中进行的三波小组调查使我们能够解开友谊网络对个人媒体使用的影响(RQ1)以及媒体使用对友谊关系的发展和维持的影响(RQ2)。基于动态社交网络分析的多层次方法并应用随机面向演员的建模,我们找到了关于电视节目和 YouTube 频道的社会影响过程的经验证据。没有发现对假设的社会选择过程的支持。除了这些实证见解外,研究设计还展示了个人行为的微观层面如何与社会群体的中观层面联系起来。此外,这些见解可以用作理解社会和媒体市场宏观层面上出现的更大规模现象的基础,例如受众碎片化和跨媒体内容的长尾受众分布。

更新日期:2020-04-19
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