Industry Influence in High-Profile Social Media Research

Abstract

To what extent is social media research independent from industry influence? Leveraging openly available data, we show that half of the research published in top journals has disclosable ties to industry in the form of prior funding, collaboration, or employment. However, the majority of these ties go undisclosed in the published research. These trends do not arise from broad scientific engagement with industry, but rather from a select group of scientists who maintain long-lasting relationships with industry. Undisclosed ties to industry are common not just among authors, but among reviewers and academic editors during manuscript evaluation. Further, industry-tied research garners more attention within the academy, among policymakers, on social media, and in the news. Finally, we find evidence that industry ties are associated with a topical focus away from impacts of platform-scale features. Together, these findings suggest industry influence in social media research is extensive, impactful, and often opaque. Going forward there is a need to strengthen disclosure norms and implement policies to ensure the visibility of independent research, and the integrity of industry supported research.

Figures (4)

• Figure 1: Article-level descriptive statistics. A) Disclosable ties that were either indicated by author affiliation (Industry), indicated in competing interest statements (Disclosed), found somewhere in the manuscript (Identifiable), found through our broader search (Found), or any combination of the above (Any). B) Percentage of papers with various sorts of disclosable industry connections C) Time-series of total articles with various disclosable ties D) Comparison of altmetric and citation impact. Values indicate the relative impact of papers with disclosable ties compared to research presumed to be independent. Vertical lines indicate 95% credible regions.
• Figure 2: Author-level descriptive statistics. A) The percentage of authors possessing a given type of tie to industry. B) The percentage of authors engaging with each firm C) Lorenz curve showing inequality in access to industry funding and collaboration, as measured in total years of funding and collaboration per firm D) Rate of disclosure as a function of the number of years in which an author was employed by, funded by, or collaborated with industry. Shaded bands correspond to the 50, 75, 89, and 95% credible regions for the expected probability. E) The probability of an author having at least one disclosable tie as a function of the number of papers on social media published in high-profile journals.
• Figure 3: A) The probability that an editor has a disclosable tie to industry as a function of the number of social media papers handled B) For papers, the probability that a paper with an academic editor has editor ties, author ties, both, or either
• Figure 4: A) Proportion of papers with ties to industry across the five topical communities identified by bibliographic coupling B) Dots indicate per-paper relative impact of the industry-connected misinformation sharing group and the more independent platform dynamics group. Vertical lines indicate 95% Credible regions.