'I See Something You Don't See'. A Computational Analysis of the Digital Services Act and the Digital Markets Act

Abstract

In its latest proposals, the Digital Markets Act (DMA) and Digital Services
Act (DSA), the European Commission puts forward several new obligations for
online intermediaries, especially large online platforms and “gatekeepers.” Both
are expected to serve as a blueprint for regulation in the United States, where
lawmakers have also been investigating competition on digital platforms and new
antitrust laws passed the House Judiciary Committee as of June 11, 2021. This Article
investigates whether all stakeholder groups share the same understanding and use
of the relevant terms and concepts of the DSA and DMA. Leveraging the power of
computational text analysis, we find significant differences in the employment of
terms like “gatekeepers,” “self-preferencing,” “collusion,” and others in the position
papers of the consultation process that informed the drafting of the two latest
Commission proposals. Added to that, sentiment analysis shows that in some cases
these differences also come with dissimilar attitudes. While this may not be
surprising for new concepts such as gatekeepers or self-preferencing, the same is
not true for other terms, like “self-regulatory,” which not only is used differently by
stakeholders but is also viewed more favorably by medium and big companies and
organizations than by small ones. We conclude by sketching out how different
computational text analysis tools, could be combined to provide many helpful
insights for both rulemakers and legal scholars.

Keywords: Digital Services Act, Digital Markets Act, Big Tech, Antitrust, Computational Analysis, Machine Learning, Competition, Gatekeepers, Remedies, Transparency duties

JEL Classification: K21, K24, K42,