Social Media, Algorithms, and Why I Chose Ghost

In the age of digital connection, it’s worth acknowledging both the tremendous promise and the real risks carried by social media. On one hand, platforms built to bring us together — whether across geography, culture, or discipline — can indeed foster community, spark conversation, and extend our circle of care in ways that were historically unimaginable. At the same time, however, we must look squarely at the growing body of evidence describing the unintended consequences of these systems, especially when their design begins to shape how we think, talk, research, and care about one another. As I launch this new blog space on Ghost, I want to share why I have consciously chosen to step aside from conventional social-media channels and what I hope this quieter format will bring.

One of the strongest concerns in the social-media era is how algorithms — the invisible code that selects and orders what we see — amplify polarization rather than connection. Research shows that algorithmically curated environments tend to erect echo chambers: feeds that reinforce what we already believe, while limiting exposure to contrasting views. For example, an analysis by Levy (2021) found that political-content algorithms on large platforms significantly reduce the likelihood that users will encounter counter-attitudinal news, increasing both ideological distance and affective polarization. Similarly, Himelein-Wachowiak et al. (2021) showed that algorithmic recommendation systems for people and groups increase homophily and deepen echo-chamber dynamics. A broader review by the National Academy of Medicine (2024) emphasized that algorithms—because they optimize for engagement—naturally elevate emotionally provocative content, which can magnify misinformation, reduce wellbeing, and subtly fracture civic life. The result is that tools designed to connect us can, paradoxically, divide us—reducing complexity into tribes and conversation into reinforcement loops.

In scientific and medical communities, social media has also begun to reshape the landscape of expertise. While there is tremendous value in transparency, accessibility, and interdisciplinary conversation, the gravitational pull toward brevity and virality can shift attention away from deep knowledge. A commentary in the Journal of Science Communication(Jensen 2024) argued that science communication on social media increasingly rewards charisma, narrative, and emotional resonance over methodological rigor or careful explanation. At the same time, contemporary health-communication studies describe the rise of “digital opinion leaders” (Patel et al. 2024)—professionals who become influencers, whose reach is determined not by the depth of scholarship but by algorithmic amplification. This is not a failure of individuals; it is a structural issue. When systems reward visibility over reflection, even well-intentioned experts may unconsciously adapt. Scientific discourse risks becoming narrower, shallower, more reactive, and more dependent on a small number of algorithmically elevated voices.

All of this brings me back to why I chose Ghost for my own writing. I cherish connection, shared insight, and the opportunity to think together. But I also believe that meaningful reflection requires space, time, and the absence of algorithmic incentives. In creating a small, quiet home outside the currents of recommendation engines, I hope to preserve a sense of intentionality—a place where ideas are not optimized for clicks but offered with sincerity. Here, I hope we can talk about medicine, life, society, caring, and caring for one another without competing for engagement metrics or filtering every thought through “what will perform well?” Instead, this can be a space for depth, curiosity, gentleness, and presence.

Most importantly, I want to emphasize respect for everyone who uses social media differently. For many, these platforms are vital tools for community, advocacy, research sharing, and belonging. I honor that. The intention here is not to critique individuals but to reflect on the environment we are all navigating. This blog is simply a complement — a slower, quieter space where conversation can be shaped by intention rather than algorithms. Thank you for being here, and thank you for choosing to read.

My next write-up will be about kindness.

References

• Himelein-Wachowiak, M., et al. (2021). “Echo chambers in algorithmic people-recommendation systems.” arXiv preprint arXiv:2112.00626.
• Jensen, E. (2024). “Science communication in the age of influencers.” Journal of Science Communication, 24(5).
• Levy, R. (2021). “Social media, news consumption, and political polarization.” American Economic Review, 111(3).
• National Academy of Medicine (2024). “Digital Opinion Leadership in the Age of Social Media and Generative AI.” NAM Perspectives.
• Patel, S., et al. (2024). “Influencers and digital opinion leadership in health communication.” NAM/Health Communication Science Initiative.