Using social media data for statistical analysis of general population faces commonly two basic obstacles: firstly, social media data are collected for different objects than the population units of interest; secondly, the relevant measures are typically not available directly but need to be extracted by algorithms or machine learning techniques. In this paper we examine and summarise two existing approaches to statistical analysis based on social media data, which can be discerned in the literature. In the first approach, analysis is applied to the social media data that are organised around the objects directly observed in the data; in the second one, a different analysis is applied to a constructed pseudo survey dataset, aimed to transform the observed social media data to a set of units from the target population. We elaborate systematically the relevant data quality frameworks, exemplify their applications, and highlight some typical challenges associated with social media data.

中文翻译：

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社交媒体数据统计分析的两种现有方法

使用社交媒体数据对一般人群进行统计分析通常面临两个基本障碍：首先，社交媒体数据是针对与感兴趣的人口单位不同的对象收集的；其次，相关度量通常不能直接获得，而是需要通过算法或机器学习技术提取。在本文中，我们检查并总结了两种现有的基于社交媒体数据的统计分析方法，这在文献中可以看出。在第一种方法中，分析应用于围绕数据中直接观察到的对象组织的社交媒体数据；在第二个中，不同的分析应用于构建的伪调查数据集，旨在将观察到的社交媒体数据转换为来自目标人群的一组单位。