Nearly a third of social media research has undisclosed ties to industry

Industry Ties in Social Media Research

• Many commenters say the findings are unsurprising and mirror patterns in tobacco, fossil fuels, pharma, food, AI, and crypto.
• Some argue industry funding is almost inevitable: they hold the data, infrastructure, and money; without them, little large‑scale research would be possible.
• Others stress this creates serious worries for policy-making, since there’s a built‑in incentive not to anger funders.
• A minority questions the study’s methodology, especially counting prior co-authorship with an industry employee as a “tie” that must be disclosed.

Trust, Disclosure, and Independence

• Several express deep distrust of both industry and academia, seeing universities as “reputation laundering” for corporate interests.
• Others emphasize that undisclosed ties call for closer scrutiny of findings, but don’t automatically invalidate results.
• A coalition for independent tech research is mentioned as an attempt to counterbalance corporate influence.

Ethics and Regulation of Corporate “Research”

• Strong concern that social media companies can run large‑scale behavioral experiments without independent ethics review, unlike academic researchers.
• Debate over what “research” actually is:
  • One side argues A/B tests and emotion‑manipulation studies clearly qualify and should face oversight.
  • The other side warns that over‑regulation would block useful analysis (including detecting harms) and notes that everyday business experimentation resembles research.
• Some see academic ethics boards as overbearing but necessary given past abuses.

Social Media as a Grand Experiment

• Many frame social media as a massive, poorly regulated experiment in connecting everyone and optimizing for engagement, outrage, and emotionalism.
• Comparisons to leaded gasoline and big tobacco: slow, large‑scale harm whose full cost may only be clear decades later.
• Extended discussion of algorithmic feeds:
  • Critics: they amplify rage, create echo chambers, normalize extremism, and differ from earlier forums by making toxicity the default rather than an opt‑in subculture.
  • Others note toxicity long predates algorithms (Usenet, forums, cable news, yellow journalism); algorithms mainly scale and automate it.

Coping and Policy Ideas

• Personal responses: delete apps, add “friction,” use non‑algorithmic tools (newsletters, chronological feeds).
• Policy suggestions: stronger disclosure norms, data transparency, limits on platform data ownership, structural reforms to reduce monopoly power, and rethinking the balance between free speech, Section 230, and algorithmic editorial control.