Media & Technology in Society

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Social media effects, digital culture, technology's societal impact, and media studies. Sub-rubric of the former Social Sciences catch-all.

The "Media & Technology in Society" section examines the friction between human behavior and the digital infrastructure that shapes modern life. By combining sociological theory with behavioral data, our research investigates how algorithms, platform architectures, and artificial intelligence redefine our cognitive, social, and institutional landscapes.

At the individual level, we explore how digital ecosystems impact mental health, identity, and interpersonal connection. This includes analyzing the psychological drivers of doomscrolling, upward social comparison on visual platforms, and the rise of technology-induced health anxiety driven by self-optimization trackers. Our research evaluates the efficacy of interventions ranging from digital detoxes to policy-level teen social media bans, while also examining the shifting dynamics of modern relationships—from the visual metrics of dating apps to the rising complexity of parasocial bonds with celebrities, fictional characters, and AI entities. Additionally, we analyze the collective dynamics of digital herd behavior, online shaming, and cancel culture.

On a systemic level, we dissect the mechanics of information diffusion and platform design. Research in this section unpacks how recommendation engines and network topologies exploit high-arousal emotions like anger and awe, causing misinformation, conspiracy theories, and outrage to outpace factual corrections. We detail the structured lifecycles of virality, the influence of information superspreaders, and practical cognitive frameworks like the SIFT method and lateral reading to counter digital science-washing.

Finally, we look toward structural and institutional disruption. This includes assessing the rise of the creator economy, the trajectory of technology adoption, and future scenarios for social media architecture, privacy, and state surveillance. Crucially, we investigate how autonomous AI agents and algorithmic credentialing are challenging the traditional value of university degrees, while warning of the risks of digital redlining and widening socioeconomic achievement gaps.

52 published articles