Investigating Heterogeneity in (Social) Media Effects: Experience-Based Recommendations

Patti M. Valkenburg, Ine Beyens, L. Keijsers
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引用次数: 1

Abstract

We recently introduced a new, unified approach to investigate the effects of social media use on well-being. Using experience sampling methods among sizeable samples of respondents, our unified approach combines the strengths of nomothetic methods of analysis (e.g., mean comparisons, regression models), which are suited to understand group averages and generalize to populations, with idiographic methods of analysis (e.g., N=1 time series analyses), which are suitable to assess the effects of social media use on each single person (i.e., person-specific effects). Our approach challenges existing knowledge of media effects based on the nomothetic-only approach. As with many innovations, our approach has raised questions. In this article, we discuss our experience with our unified media effects approach that we have been building since 2018. We will explain what our approach exactly entails and what it requires. For example, how many observations are needed per person? Which methods did we employ to assess the meaningfulness of variation around average effects? How can we generalize our findings to our target populations? And how can our person-specific results aid policy decisions? Finally, we hope to answer questions of colleagues who are interested in replicating, extending, or building on our work.
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调查(社交)媒体效应的异质性:基于经验的建议
我们最近推出了一种新的统一方法来研究社交媒体的使用对幸福感的影响。我们的统一方法采用在相当大的受访者样本中进行经验抽样的方法,结合了名义分析方法(如均值比较、回归模型)和特异分析方法(如 N=1 时间序列分析)的优势,前者适合了解群体平均值并对群体进行概括,后者适合评估社交媒体使用对每个人的影响(即针对个人的影响)。我们的方法对现有的基于唯名论的媒体效应知识提出了挑战。与许多创新一样,我们的方法也引发了质疑。在本文中,我们将讨论我们自 2018 年以来建立的统一媒体效果方法的经验。我们将解释我们的方法具体包含哪些内容,需要哪些条件。例如,每人需要多少次观察?我们采用了哪些方法来评估平均效应周围变化的意义?如何将我们的研究结果推广到目标人群?我们针对特定人群的结果如何帮助政策决策?最后,我们希望能回答那些有兴趣复制、扩展或发展我们工作的同行的问题。
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