But did they really? Platforms' compliance with the code of practice on disinformation in review

Mündges, Stephan; Park, Kirsty Article But did they really? Platforms' compliance with the code of practice on disinformation in review Internet Policy Review Provided in Cooperation with: Alexander von Humboldt Institute for Internet and Society (HIIG), Berlin Suggested Citation: Mündges, Stephan; Park, Kirsty (2024) : But did they really? Platforms' compliance with the code of practice on disinformation in review, Internet Policy Review, ISSN 2197-6775, Alexander von Humboldt Institute for Internet and Society, Berlin, Vol. 13, Iss. 3, pp. 1-21, https://doi.org/10.14763/2024.3.1786 This Version is available at: https://hdl.handle.net/10419/300750 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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Platforms’ compliance with the Code of Practice on Disinformation in review Stephan Mündges TU Dortmund University Kirsty Park European Digital Media Observatory DOI: https://doi.org/10.14763/2024.3.1786 Published: 25 July 2024 Received: 28 December 2023 Accepted: 27 March 2024 Funding: Kirsty Park received funding for this research from the European Union under action number 2020-EU-IA-0282 and agreement number INEA/CEF/ICT/A2020/ 2381686, Stephan Mündges received funding for this research from the European Union, project number 101083573. Competing Interests: The author has declared that no competing interests exist that have influenced the text. Licence: This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 License (Germany) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. https://creativecommons.org/licenses/by/3.0/de/deed.en Copyright remains with the author(s). Citation: Mündges, S. & Park, K. (2024). But did they really? Platforms’ compliance with the Code of Practice on Disinformation in review. Internet Policy Review, 13(3). https://doi.org/10.14763/2024.3.1786 Keywords: Disinformation, Platform regulation, Code of Practice on Disinformation, EU internet policy, VLOP Abstract: A key pillar in the EU’s approach to regulating disinformation is the Strengthened Code of Practice on Disinformation. This self-regulatory Code proposes a broad range of measures for different stakeholders. It has been signed by platform companies that thereby agreed to report on compliance with the Code. This study investigates Google’s, Meta’s, Microsoft’s, TikTok’s and Twitter’s (now X) compliance with their reporting obligations for the first time. Analysing the platform baseline reports published in early 2023, we find that, overall, platforms are only partly compliant with the Code. Qualitative information provided by platforms often lack detail and/or relevance. Reported quantitative data is, in several cases, missing, incomplete, or not robust. We point out claims by platforms that are doubtful or have been proven wrong in the past, and highlight avenues for future research and investigations. Additionally, we reflect on the framework in place for monitoring the Code of Practice and ways to improve it. This study is particularly relevant as the EU is transitioning from a self-regulatory to a co-regulatory model when regulating disinformation. The Code of Practice may soon become a code of conduct under the Digital Services Act (DSA) making non-compliance with it sanctionable and increasing the need for systematic monitoring. Issue 3 Introduction Disand misinformation is considered by many scholars, journalists, and policymakers to be a substantial threat to democratic systems and public discourse (Lewandowsky et al., 2017; van der Linden, 2023). There is debate within academia regarding the scope of this challenge, with some scholars noting that empirical evidence for the prevalence of misand disinformation and how it influences public attitudes, behaviours, and participation in political processes is contentious (Altay et al., 2023; Altay et al., 2022; Jungherr & Schroeder, 2021). However, other findings indicate that false claims and misinformation are indeed quite prevalent, particularly, on digital platforms (Yang et al., 2023; Ecker et al., 2024). Independent of this academic debate, several political actors have taken action to counter misand disinformation, hinder its spread in digital information spaces and – in some instances – penalise actors publishing disinformation (Cipers et al., 2023). Among democratic political systems, the European Union is arguably the most prominent and most active in this regard. Apart from non-legislative actions (e.g. more strategic communication, more funding for media literacy programmes), it has initiated the Strengthened Code of Practice on Disinformation (hereinafter referred to as ‘the Code’ or ‘the CoP’), a self-regulatory framework signed by the major technology companies (Google, Meta, Microsoft, TikTok), among others (CoP, 2022). By becoming signatories, platforms commit to take numerous very specific actions to counter misand disinformation on their services. The Code is detailed and wide-ranging, covering fields such as political advertising, recommendation systems, and support for researchers and fact-checkers. Thus, the reporting that the signatories of the Code publish biannually is extensive. Even though only a voluntary commitment by the platforms, the Code is a regulatory instrument which may help to provide transparency about disinformation on large online platforms, but the extent of this transparency requires systematic monitoring. This study summarises data and findings of such a monitoring, that was carried out as a pan-European collaboration by independent academic researchers and has been reported to stakeholders (Park & Mündges, 2023). Assessments of signatories’ compliance with certain parts of the Code have been conducted by other stakeholders (EFCSN, 2023; Kiely et al., 2023), but, to our knowledge, this is the first comprehensive monitoring of the Code’s platform signatories. For this, we developed a monitoring framework which we applied to the first set of signatory reports which were published in early 2023. Our analysis provides insights into platforms’ compliance with the Code but also offers valuable lessons for future monitoring of similar policy instruments and may be instructive for ongoing formal 2 Internet Policy Review 13(3) | 2024 proceedings against VLOPs. This is particularly relevant as the Code of Practice on Disinformation might become a Code of Conduct, and hence turn into a legal imperative, under the Digital Services Act (DSA). The Code of Practice on Disinformation as a cornerstone of the EU’s response to disinformation Disinformation is a complex issue with varying definitions and the need for balancing different fundamental rights, making it challenging to regulate (Peukert, 2023). Stasi and Parcu (2021) offer three conceptual models that can be applied when regulating disinformation: TABLE 1: Regulatory models, adapted from Stasi & Parcu, 2021 MODEL DESCRIPTION STATE INFLUENCE LEVEL WEAKNESSES Statutory model Rules passed by lawmakers or regulatory bodies, enforced by the government, government agencies, or regulatory authorities strong Unlikely to keep up with fast changing technology landscape; could be used to justify censorship Coregulatory model Rules which are negotiated by those subject to them and the regulator medium Risk of regulatory capture Selfregulatory model Rules relying entirely on voluntary compliance, where legislators and regulators mainly observe private efforts and essentially play no active role weak Shift of power from public to private sector; lack of accountability; lack of protection of fundamental rights These models are, of course, not fully distinct from one another but should be thought of as a “spectrum of possibility” (Stasi & Parcu, 2021, p. 422). In the case of regulating disinformation, the EU started out with the self-regulatory model, adopting a multi-stakeholder approach, but is shifting its approach over recent years to the co-regulatory and in part statutory model. The Code was initiated by the European Commission and published in 2018, marking the first time that platforms agreed on a set of self-regulatory standards (European Commission, 2018). The text of the Code was informed by the report of the High-Level Group on fake news and online disinformation and signed by several stakeholders including advertising associations and platform companies. After its release, the Code underwent monitoring by the European Commission itself, as well as by various stakeholders, all of which concluded similar points of critique: the Code was vague concerning certain commitments and insufficiently comprehensive in others. Moreover, it was noted that the Code lacked measurable objectives, key performance indicators, and a lack of independent verification of plat3 Mündges, Park form claims (Culloty et al., 2021; European Regulators Group for Audiovisual Media Services, 2020; Stasi & Parcu, 2021). As a result, it was revised and re-published as “Strengthened Code of Practice on Disinformation” in 2022 (CoP, 2022). This new iteration incorporates numerous suggestions previously put forth by stakeholders and monitoring bodies, is better structured, more detailed, and clearer in what information must be provided. Additionally, signatories are obliged to report more granular and country-specific data. The Strengthened CoP defines disinformation broadly to encompass "misinformation, disinformation, information influence operations, and foreign interference in the information space" (CoP, 2022, p. 1). It consists of nine sections, which can be divided into three categories: reaction, empowerment, and monitoring. • Reaction: addresses monetisation of disinformation and manipulative techniques. ◦ Sections: scrutiny of ad placements, political advertising, integrity of Services. • Empowerment: mandates cooperation with stakeholders. ◦ Sections: empowering users, research community, fact-checking community. • Monitoring: details how the Code is overseen and its outcomes disseminated. ◦ Sections: transparency centre, permanent task-force, monitoring of the Code. Each section has three layers: 1. Commitments: overall objectives and actions 2. Measures: specific steps for Signatories 3. Reporting elements: either "Qualitative Reporting Elements" (QRE) or quantifiable "Service Level Indicators" (SLI); they detail what signatories have to report in order to prove compliance with measures For example, commitment 27 obliges platforms “to provide vetted researchers with access to data necessary to undertake research on Disinformation by developing, funding, and cooperating with an independent, third-party body that can vet researchers and research proposals” which is operationalized in four measures: to contribute to the development of the aforementioned independent third-party body (measure 27.1); commit to co-fund this body (27.2): work with this third-party body “to enable sharing of personal data necessary to undertake research on Disinformation with vetted researchers” (27.3); engage in pilot programs for granting data access to researchers without the third-party body being set up (27.4). For 4 Internet Policy Review 13(3) | 2024 each measure signatories have to report qualitative information, specified in the corresponding QREs (e.g. QRE 27.2.1: disclose funding for the development of the third-party body), and for measure 27.3 they also have to report quantitative data about the number of research projects which have been granted data access. Currently, the Code includes 44 commitments which are operationalized in 128 measures. It has been signed by 44 stakeholders, including big tech companies Google, Meta, Microsoft, and TikTok. Twitter (now called X; as the platform committed to the Code as Twitter this name is used throughout this paper) had been a signatory until May 2023 but the company decided to leave the Code under its new owner Elon Musk. Given its design, it is evident the CoP primarily aims to regulate Big Tech's role in disinformation dissemination. By signing the Code, signatories commit to report regularly, every six months in the case of signatories that qualify as Very Large Online Platforms (VLOPs) or Search Engines (VLOSEs) under the DSA, on their compliance with the Code. They do so using a predefined reporting template which enables both quantitative as well as qualitative comparisons between signatories. The template was developed by representatives of the European Regulators Group for Audiovisual Media Services (ERGA) that are part of the CoP Permanent Task-force in consultation with the signatories. Participation in the Code is voluntary. However, the DSA will introduce obligations for VLOPs and VLOSEs defined as platforms with more than 45 million users in the EU. The DSA's Article 45 commends the formulation of voluntary codes of conduct, referencing the CoP as a potential example (Regulation 2022/2065, 106). Concretely, article 45(1) tasks the Commission and the European Board for Digital Services with promoting and facilitating the creation of codes of conduct to ensure proper application of the DSA, particularly addressing the challenges of systemic risks. Article 45(2) states that if significant systemic risks involving several VLOPs and/or VLOSEs arise, the Commission may invite stakeholders to develop codes with specific risk mitigation measures and a reporting framework. Hence, codes of conduct are particularly relevant for VLOPs and VLOSEs in fulfilling two cornerstone articles of the DSA, namely articles 34 “Risk assessment” and 35 “Mitigation of risks”. Risk assessments must encompass various issues. Although the article does not explicitly mention disinformation, it implies comprehensive coverage of the phenomenon by including “any actual or foreseeable negative effects on civic discourse and electoral processes, and public security” (Art. 34(1)(c)). Mitigation measures must be taken by VLOPs and VLOSEs if systemic risks are identified in the assessments conducted as part of article 34. These measures may include modifying service designs and features, updating terms and conditions, im5 Mündges, Park proving content moderation processes to quickly address illegal content, or adjusting “internal processes, resources, testing, documentation, or supervision of any of their activities in particular as regards detection of systemic risk” (Art. 35(1)(f)). Codes of conduct offer the opportunity to specify these broad obligations and operationalise them into specific commitments. Additionally, they may provide detailed standards to facilitate internal compliance and external assessments, give a diverse set of stakeholders the chance to shape DSA implementation and allow for future action and adaptation to technological progress by addressing areas or gaps not covered in the DSA. While these codes are soft law instruments and will continue to be voluntary, the DSA does specify that non-compliance with codes may attract penalties, which is a much bigger incentive for major platforms to cooperate (Griffin & Vander Maelen, 2023) and signals the EU’s shift from a selfto a co-regulatory model when regulating disinformation. As a probable inaugural code under the DSA, it is crucial for the CoP to be unambiguous, strictly adhered to, and consistently monitored. Considering the broad scope of the CoP, its focus on very large digital platforms and the relevance of monitoring compliance systematically, we ask two research questions: RQ1: To what extent do platform signatories of the Code comply with their reporting obligations? RQ2: How can compliance with the CoP be monitored systematically, regularly and comprehensively? Method This analysis centres on platform signatories classified as VLOPs/VLOSEs under the DSA, which are Google, Meta, Microsoft, TikTok, and Twitter. These platforms are often exploited by malicious entities and unsuspecting users to disseminate disinformation and misinformation. Given their vast user bases, they warrant significant scrutiny. To answer RQ1 we analysed the first set of CoP reports published by the platforms in early 2023. The reports are extensive (859 pages in total) but the structure of the predetermined reporting template enabled robust comparisons of signatory reports. We opted to analyse at the measure level, viewing commitments as too overarching and reporting elements as overly granular. In our analysis we drew from content analysis methodology (Puppis, 2019). We for6 Internet Policy Review 13(3) | 2024 mulated a customised coding scheme, incorporating three quantitative and two qualitative metrics, detailed in the subsequent table. TABLE 2: Coding scheme VARIABLE EXPRESSION EXPLANATION MISSING QUALITATIVE RESPONSES yes Information that is requested in a Measure or QRE is not provided comprehensively, and/or the information provided by the Signatory does not meet the obligations set out in the Measure or QRE. As some QREs cover several aspects of an issue, this variable should also be coded as “yes” when the Signatory fails to provide information of one or more relevant aspects. no The qualitative responses provided by the Signatory are comprehensive, concise and to the point. irrelevant If a Measure does not contain QREs, this variable might be coded irrelevant. MISSING QUANTITATIVE DATA yes SLIs are ignored or relevant data that is requested as part of a Measure or SLI is not provided by the Signatory. This might also be the case if Member State specific data is requested but not provided. The variable is also to be coded “yes” if data provided is unsuitable or the methodology is ill-suited to provide reliable data. no Quantitative data provided by the Signatory is comprehensive and the methodology to collect or calculate the data is appropriate. irrelevant Measure does not contain SLI or there is reasonable ground why an SLI cannot be provided at this point in time. OVERALL SCORE 1 Poor: the response significantly falls short of meeting the requirements of the Measure. This is the case for responses that lack major details, are incomplete or irrelevant, or fail to address the specific information requests outlined in the measure. 2 Adequate: the response shows effort towards meeting the requirements of the Measure but there are notable issues or areas that require improvement. This is the case for responses that partially address the question, but may lack important details, evidence, or context. 3 Good: the response fully meets the requirements of the Measure. This is the case for responses that are complete, relevant, and provide clear and comprehensive information that directly addresses the specific information requests outlined in the measure. n/a Not Applicable: if a Signatory claims a Measure they subscribed to is not relevant to their services and the Assessor believes this claim to be correct e.g. the Measure relates to displaying information alongside political advertising and the Signatory's product does not allow political advertising. SIGNATORY LEVEL COMMENTS free text Qualitative comments explaining the Coder’s results for the previous three variables, e.g. “lacked detail on x”. Coders should include any observations or feedback on the response. CODE LEVEL COMMENTS free text Qualitative comments regarding the CoP; this might include comments on wording, structure, needed clarification, etc. For coding, we adopted a three-step process. Initially, two coders independently analysed specific sections, with the option to flag uncertain codings as "needs a second opinion". After these initial rounds, a third round sought to finalise the results. The lead authors reviewed all discrepancies between the initial coders, refer7 Mündges, Park encing comments and reports content to determine the final outcome. Additionally, they reviewed all codings for inconsistencies. We present numerical outcomes for the first six sections. For the final three, focused on the Code's monitoring methods, we offer general remarks without numerical data, as many measures lacked distinct reporting elements or were absent entirely. From our qualitative analysis of the last three sections as well as from insights gained through the coding process for the first six sections we draw conclusions to offer potential answers to RQ2. Results for RQ1: Assessment of platforms’ compliance with the Code of Practice on Disinformation TABLE 3: Overall scores per signatory (scores correspond to grades of 1 = Poor, 2 = Adequate and 3 = Good) SIGNATORIES % OF MEASURES MISSING QUALITATIVE INFORMATION % OF MEASURES MISSING QUANTITATIVE DATA AVERAGE OVERALL SCORE Google 44% 53% 2.1 Meta 52% 65% 2.0 Microsoft 54% 59% 1.9 TikTok 43% 50% 2.0 TOTAL w/o Twitter 49% 58% 2.0 Twitter 100% 100% 1.0 TOTAL 55% 64% 1.9 The average score of signatories is a subpar 1.9, with only Google exceeding an overall grade of 2 (Adequate) at 2.1. Measures containing QREs revealed that 55% (with Twitter excluded 49%) were either incomplete or lacked qualitative information, while 64% (with Twitter excluded 58%) of Measures with SLIs were lacking at least some data. Twitter left the Code in May 2023, so several months after the baseline reports had been published (Hendrix, 2023). Evidence suggests its commitment was waning well before its exit, averaging the lowest possible score 1 (Poor) and exhibiting a 100% deficiency in QREs/SLIs across all measures. The report contained numerous empty sections, limited general comments on some commitments, and information that often seemed directly copied from their website. This suggests Twitter had little intention of adhering to the Code when reporting. 8 Internet Policy Review 13(3) | 2024 Twitter under the DSA citing shortcomings of “measures taken to combat information manipulation on the platform” (European Commission, 2023). Regarding the remaining platforms, the information and responses provided often fail to precisely address the Code's specific requirements, with many instances of incomplete information. The reporting of quantitative data requires significant improvement in both scope and detail. The methodologies for calculating quantitative data need to be more accurate, with an emphasis on providing member statelevel data. It is crucial to emphasise that our analysis must be regularly replicated and refined to maximise its utility for policy evaluation and enforcement. We encourage researchers to build upon and apply our methodological framework to other platform reports on compliance with the CoP. We believe it is easily replicable and platform-agnostic, i.e. if more VLOPs or VLOSEs join the Code their reports can be analysed applying the same methodological framework. Signatories and regulators should pay special attention to ensuring comparable methodologies when reporting SLIs. Although challenging, due to the platforms' differing focuses, metrics, and specifications that complicate comparisons, there are still data points that allow for comparisons (e.g. related to TTPs). Additionally, the data currently hidden in platform reports could be integrated into the DSA Transparency Database2 and made available in a machine-readable format. Repeated research over time will yield invaluable insights into how platforms evolve in countering disinformation, how the implementation of the DSA influences their policies and enforcement actions, and their overall behaviour. This iterative process will refine the methodology, identify gaps in platform reporting, and highlight statements that warrant further investigation. This will be particularly significant when the Code of Practice transitions into a code of conduct under the DSA. As it is likely to be the first one, the way this transition is managed, its impact, and its implementation by regulators and policymakers will largely determine the DSA's effectiveness in regulating harmful but mostly lawful speech. Given recent developments and investigations initiated by the European Commission into the behaviour and policies of very large online platforms, the importance of this work cannot be overstated. In its press release announcing the opening of formal proceedings against Meta, the European Commission mentions specifically 2. See European Commission (n.d.). 15 Mündges, Park that it “suspects that Meta does not comply with DSA obligations related to addressing the dissemination of deceptive advertisements, disinformation campaigns and coordinated inauthentic behaviour in the EU” (European Commission, 2024). Monitoring compliance with the Code of Practice may offer valuable insights for such investigations and indicate areas where platforms fall short in their responsibility to counter disinformation. Even though our analysis was focussed on monitoring compliance with reporting obligations, we found several instances in which platforms’ claims are at least doubtful if not even contradicted by already published empirical evidence. Areas of concern are the enforcement of bans on political advertisements and actions against fake engagement and inauthentic behaviour. Therefore, future monitoring should be accompanied by in-depth investigations into specific focus areas to further enhance our understanding and improve regulatory practices. The European Commission should ensure this monitoring is adequately funded and resourced long-term, conducted by independent researchers with the necessary background knowledge. Only after these steps towards a systematic monitoring have been taken, will we be able to answer with certainty the question: but did platforms really do what they claim to have done? Limitations While this study provides valuable insights into platforms’ compliance with the CoP, it is essential to acknowledge certain limitations. Firstly, our analysis is based on the initial set of reports published by platform signatories in early 2023. Since then, these signatories have published a second round of reports in September 2023. Our results do not reflect any changes to reporting compliance through these reports. Secondly, the monitoring framework developed for this analysis, while comprehensive, may have inherent subjectivity in its assessment criteria. The interpretation of policy compliance and reporting quality can vary. Through application of a three-step coding process we try to minimise this subjectivity but may not eliminate it entirely. Thirdly, the analysis is focused on monitoring compliance with reporting obligations. It does not comprehensively assess the accuracy of information and data reported by signatories. As noted, we identified several instances in which accuracy is at least doubtful. This calls for more investigatory approaches to monitor CoP compliance. Lastly, the analysis focuses on platform signatories, and the findings may not generalise to platforms that are not (yet) signatories of the Code. 16 Internet Policy Review 13(3) | 2024 ACKNOWLEDGEMENTS The authors thank all colleagues who contributed to the analysis of platform reports and gave feedback during the drafting of the article: Mato Brautović, University of Dubrovnik Eileen Culloty, Dublin City University Dawn Holford, University of Bristol Anastasia Kozyreva, Max Planck Institute for Human Development Stephan Lewandowsky, University of Bristol, University of Potsdam, and University of Western Australia Trisha Meyer, Vrije Universiteit Brussel Susanne Wegner, TU Dortmund University Kirsty Park and Eillen Culloty received co-funding for this research from the European Union under action number 2020-EU-IA-0282 and agreement number INEA/CEF/ICT/A2020/2381686. Susanne Wegner and Stephan Mündges received co-funding for this research from the European Union, project number 101083573. Mato Brautović received co-funding for this research from the European Union, project number 101083909. Trisha Meyer received co-funding for this research from the European Union, project number INEA/CEF/ICT/A2020/2394296. Stephan Lewandowsky has received funding from Jigsaw (a technology incubator created by Google) for several empirical projects unrelated to the present paper. He also acknowledges financial support from the European Research Council (ERC Advanced Grant 101020961 PRODEMINFO) and the European Commission (Horizon 2020 grants 964728 JITSUVAX and 101094752 SoMe4Dem). He also receives support from UK Research and Innovation (through EU Horizon replacement funding grant number 10049415). 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