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Censuses around the world are key sources of data to guide governmentinvestments and public policies. However, these sources are very expensive toobtain and are collected relatively infrequently. Over the last decade, therehas been growing interest in the use of data from social media to complementtraditional data sources. However, social media users are not representative ofthe general population. Thus, analyses based on social media data requirestatistical adjustments, like post-stratification, in order to remove the biasand make solid statistical claims. These adjustments are possible only when wehave information about the frequency of demographic groups using social media.These data, when compared with official statistics, enable researchers toproduce appropriate statistical correction factors. In this paper, we leveragethe Facebook advertising platform to compile the equivalent of anaggregate-level census of Facebook users. Our compilation includes thepopulation distribution for seven demographic attributes such as gender and ageat different geographic levels for the US. By comparing the Facebook countswith official reports provided by the US Census and Gallup, we found very highcorrelations, especially for political leaning and race. We also identifiedinstances where official statistics may be underestimating population counts asin the case of immigration. We use the information collected to calculate biascorrection factors for all computed attributes in order to evaluate the extentto which different demographic groups are more or less represented on Facebook.We provide the first comprehensive analysis for assessing biases in Facebookusers across several dimensions. This information can be used to generatebias-adjusted population estimates and demographic counts in a timely way andat fine geographic granularity in between data releases of official statistics

How Biased is the Population of Facebook Users? Comparing the Demographics of Facebook Users with Census Data to Generate Correction Factors