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Using social media data for statistical analysis of general population facescommonly two basic obstacles: firstly, social media data are collected fordifferent objects than the population units of interest; secondly, the relevantmeasures are typically not available directly but need to be extracted byalgorithms or machine learning techniques. In this paper we examine andsummarise two existing approaches to statistical analysis based on social mediadata, which can be discerned in the literature. In the first approach, analysisis applied to the social media data that are organised around the objectsdirectly observed in the data; in the second one, a different analysis isapplied to a constructed pseudo survey dataset, aimed to transform the observedsocial media data to a set of units from the target population. We elaboratesystematically the relevant data quality frameworks, exemplify theirapplications, and highlight some typical challenges associated with socialmedia data.

On two existing approaches to statistical analysis of social media data