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Biases create prejudice and discrimination against certain groups or people. Harm can also result from the intentional exploitation of (consumer) biases, or by engaging in unfair competition, such as the homogenization of prices by means of collusion or a non-transparent market. Using data gathered through social networks could contribute to exacerbate such a situation mainly by building biased datasets. This might happen, for instance, due to an inadequate collection of the data produced by the data subjects. “Social media data can be difficult to verify – users may lie about their age, location, job, or any number of other characteristics. Researchers must be aware of this issue and address this difficulty where relevant. It is not advisable to understand users as the ‘general public’, due to inequalities in access to the internet, and researchers should consider how to foster diversity (where relevant) in their sample.”[1] It might also happen that inferred or derived data create such biases due to their own technical issues. If these biased data fuel profiling or automated decision making, this could bring unacceptable social consequences. Of course, if the research involves the use of AI, this will probably increase the risk related to biases(see the “Lawfulness, fairness and Transparency” subsection of the Main Principles section of the General Part of these Guidelines).

In order to avoid such a scenario, critical assessment of the provenance of the data is required. To this purpose, organizational measures should be implemented to guarantee the accuracy and reliability of the gathered data, while still ultimately deferring to the right of users to withhold private information (e.g. confirming whether or not a record is accurate). Furthermore, performing an audit devoted to detecting biases in raw data or in the inferred or derived datasets is required especially when controllers are using datasets produced via social networks.


1Univerity of York, Guidelines for the Use of Social Media Data in Research, at:


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