How Social Media Platforms Influence Academic Research, and How to Address it

Imagine if food or drug companies were allowed to hide the ingredients of their products from independent researchers. In a new comment published in Humanities and Social Sciences Communications, Isabelle Freiling and I argue that this is exactly the situation with social media platforms — and it can exacerbate forms of industry influence that have long been documented in other fields.

Social media platforms are no longer just objects of research — they are increasingly data gatekeepers and research funders. This creates a structural conflict of interest, especially when platforms engage in research on issues in which they have a direct stake, such as whether they contribute to political polarization or misinformation, and how these problems should be addressed. A recent preprint shows that many of these material connections are in fact not disclosed, which is highly problematic (Bak-Coleman et al., 2026). However, the conflicts created often cannot be resolved by disclosure alone.

In this comment, we argue that the problem goes beyond disclosure (Heiss & Freiling, 2026). Even research in which conflicts are formally disclosed can still be subject to systematic bias, and there is substantial evidence that this is indeed the case. While large-scale private funding of social science research is relatively new, other disciplines have been dealing with industry influence for decades. In response, they have developed a strong tradition of meta-research examining how funding sources shape research agendas and results.

The findings are striking. For instance, a meta-analysis in nutrition research on the relationship between sugar-sweetened beverages and obesity or type 2 diabetes found that almost all industry-funded studies concluded that sugary drinks do not increase obesity or diabetes — while nearly all independent studies reported the opposite (Schillinger et al., 2016).

How Industry Influence Operates

Industry influence on research can operate at any stage of the research cycle (Bero, 2023). For example, through targeted funding calls, industry actors can shape research agendas and even define the questions that academics work on. They can also selectively fund proposals they perceive as most aligned with their strategic interests.

Furthermore, funding itself and personal interactions between researchers and funders can trigger feelings of reciprocity, making researchers less willing to interpret data in ways that might harm the funding industry partner. This effect is likely to be even stronger when researchers interact directly with industry representatives. However, researchers are often not aware of the biases that may result from such interactions, and even when influence is present, it is often difficult to detect and prove.

Beyond agenda setting and interpretation, industry influence may also operate at the level of data analysis, for example through choices of variables, model specifications, inclusion and exclusion criteria, or robustness checks that are shaped by structural dependencies. Once industry-aligned research results are published, industry players can also bias science communication by selectively highlighting specific findings and disseminating them in a one-sided manner through powerful marketing channels.

In fact, there are reasons to assume that industry influence can be exerted at any stage of the research process, from agenda setting to dissemination, as illustrated in Figure 1. For social media platforms, the gate-keeping role in data access plays a particularly critical role.

Figure 1. Industry influence in social media research can operate at multiple, interconnected stages of the research process, including funding, control over data access, data analysis, interpretation of results, dissemination, and sustained relationships between platforms and researchers.

Data Access as a Unique Issue

There is no reason to assume that social media platforms do not follow similar industry interests. Compared to other industries, however, platforms have a unique advantage: they host and control access to their own data. This gives them an unprecedented form of epistemic power.

In our comment, we illustrate this problem with a simple analogy:

“Imagine if researchers were denied access to the ingredients of food products or drugs to study their effects on human health. However, when it comes to social media products, access to their “ingredients,” such as algorithms and input data, is limited.”

While in pharmaceutical or food research, scientists can generate independent data, this is not the case for platform research. Access to core information — including algorithms, content exposure, and engagement dynamics — is controlled by the companies themselves.

This issue became especially visible in the major industry–academia collaboration between Facebook and independent researchers around the 2020 US presidential election. In this collaboration, Meta provided exclusive access to internal data, and Meta researchers actively participated in the research process. This setting opened the door to potential industry influence and it later emerged that Meta had altered key algorithmic features during the field study. However, the results of the studies were highlighted on Meta’s website as robust evidence that the platform’s algorithm does not increase political polarization. The media echoed this frame.

Figure 2. Examples of media coverage following the release of the 2020 U.S. presidential election studies from the Meta–researcher collaboration.

While there is strong evidence that industry influence has biased scientific results in other fields — such as nutrition science, tobacco research, or fossil fuel studies — there is no convincing reason to assume that social media research should be immune to similar dynamics.

Institutionalization of Influence

Beyond individual projects, platforms also seek to institutionalize their influence through long-term funding schemes, fellowships, and research centers. Examples include Meta’s global early career fellowships, the Social Science One partnership, the Chan Zuckerberg Initiative’s large-scale funding of AI research, or Google’s Jigsaw.

While these initiatives may support valuable research, they also create permanent dependencies and intermediary organizations that can subtly align research agendas with corporate interests. This makes it especially important to understand the extent and impact of industry influence now — before such institutional structures become so entrenched that they are difficult to reverse.

Challenging Industry Influence

In light of this, we argue that new policies are needed. These include limiting industry collaborations in areas with clear conflicts of interest (such as misinformation, polarization, and health), and reforming how industry funding is distributed — for example, by establishing independent agencies to manage and allocate such funds. If platforms are genuinely interested in advancing knowledge independent of corporate interests, there is little reason not to delegate funding decisions to independent bodies.

In addition, stronger regulation is needed to ensure that researchers can access social media data independently. Imagine if researchers were unable to study the ingredients of food products or drugs in order to assess potential harms. In the case of social media, we face precisely this situation: access to core data is controlled by the companies themselves, forcing researchers into dependency relationships. This is highly problematic.

The EU’s Digital Services Act attempts to address this issue by requiring very large platforms to provide vetted researchers with access to internal data in order to study systemic risks such as misinformation or political polarization. While early evidence suggests that platforms often resist or delay meaningful access, the DSA represents the first serious attempt to structurally reduce researchers’ dependency on platform goodwill.

Finally — and most importantly — we need a more critical research community that systematically examines industry influence. The core risk is not only biased findings, but the gradual capture of the entire knowledge production process around social media — from research questions and data access to funding structures and institutional infrastructures. To understand and counteract this process, we need robust meta-analyses and investigative “research on research” that make industry influence visible, measurable, and contestable (see Table 1 for a summary, from Heiss & Freiling, 2026).

References

• Bak-Coleman, J., West, J., O’Connor, C., & Bergstrom, C. T. (2026). Industry influence in high-profile social media research [Preprint]. https://doi.org/10.48550/arXiv.2601.11507

• Bero, L. (2023). Industry influence on research: A cycle of bias. In N. Maani, M. Petticrew, & S. Galea (Eds.), The commercial determinants of health (pp. 185–196). Oxford University Press. https://doi.org/10.1093/oso/9780197578742.003.0019 

• Heiss, R., & Freiling, I. (2026). Addressing social media platforms’ influence on academic research. Humanities and Social Sciences Communications,13,192. https://doi.org/10.1057/s41599-026-06690-6 

• Schillinger, D., Tran, J., Mangurian, C., & Kearns, C. (2016). Do sugar-sweetened beverages cause obesity and diabetes? Annals of Internal Medicine, 165, 895–897. https://doi.org/10.7326/L16-0534

Title graph is generated with OpenAI's DALL-E.