Skip to main content

Applied Social Sciences

The practical use of sociological, anthropological, and political science theories to solve real-world problems in communities, organizations, and governments. Unlike pure social science, which seeks knowledge for its own sake, Applied Social Sciences deploy surveys, ethnographic observation, policy analysis, and program evaluation to address concrete issues: reducing recidivism, increasing voter turnout, managing urban gentrification, or improving disaster response. It is social theory with its sleeves rolled up.
Applied Social Sciences Example: A team of applied sociologists is hired by a city to understand why a new public transit line is underutilized. They don't just count riders; they conduct interviews, observe boarding patterns, and analyze fare data. Their recommendation—relocate a bus stop 200 meters to connect with a popular market—increases ridership by 40%. This isn't academic sociology; it's Applied Social Science, diagnosing and treating the social body.
Applied Social Sciences mug front
Get the Applied Social Sciences mug.
See more merch

Social Sciences Applied to Social Media

A field of study that uses sociological, anthropological, political, and economic frameworks to analyze how social media platforms shape human behavior, community formation, power dynamics, and cultural production. It examines phenomena like algorithmic governance, influencer economies, digital labor, online identity formation, and the transformation of public discourse. By applying social science tools—ethnography, network analysis, surveys, critical theory—to social media, it moves beyond superficial engagement metrics to understand how platforms mediate social life, reproduce inequality, and create new forms of belonging and exclusion.
Social Sciences Applied to Social Media Example: “Her research applied sociology to TikTok, showing how the algorithm’s preference for controversy pushed creators toward increasingly extreme content—a social science lens revealing the structural drivers of online polarization.”

AI Applied to Social Sciences

The use of artificial intelligence and machine learning as powerful new tools for social science research. This includes using large language models to analyze centuries of text, employing computer vision to study non-verbal behavior in archived footage, or building agent-based models to simulate the spread of ideas or diseases through populations. It's the computational revolution coming for sociology and anthropology, offering the ability to find patterns in data too vast for any human researcher to process.
Example: "He used to spend years interviewing people; now with AI applied to social sciences, he just feeds millions of Reddit comments into an algorithm and calls it a day."

Social Sciences Applied to AI

The practice of using insights from sociology, anthropology, psychology, and political science to design, understand, and regulate artificial intelligence. It recognizes that AI systems are not neutral math problems but are embedded in human social contexts. This field asks: How will this algorithm affect community dynamics? What social biases is it learning? How does it change power structures? It's the antidote to the naive view that AI is just code, reminding us that every AI is also a social actor.
Example: "They built a great recommendation engine, but without social sciences applied to AI, they accidentally created filter bubbles that radicalized their users."

Social Sciences Applied to the Internet

A broader field extending social science methods to the entire internet ecosystem—infrastructure, governance, political economy, and culture. It examines how internet architecture (protocols, data centers, fiber optics) embodies political values, how governance regimes (ICANN, national regulations) shape freedom, and how economic models (surveillance capitalism, gig platforms) reorganize labor and value. It treats the internet not as a neutral network but as a contested social space where power, resistance, and inequality are enacted.
Example: “His work on social sciences applied to the internet traced how the shift from net neutrality to privatized data flows concentrated economic power in a handful of platform companies, reshaping global digital rights.”

Human Sciences Applied to Social Media

A complementary field that integrates humanities disciplines—history, philosophy, literature, cultural studies, media studies—into the analysis of social media. It asks questions about meaning, narrative, identity, ethics, and historical continuity. Where social sciences focus on structures and behaviors, human sciences explore the symbolic dimensions: how social media becomes a site for storytelling, selfhood, and cultural memory. It also critically examines the philosophical assumptions built into platform design and the ethical implications of algorithmic mediation.
Example: “Using human sciences applied to social media, he analyzed how Instagram’s aesthetic norms reproduced colonial-era visual hierarchies, turning self-presentation into a politics of visibility and exclusion.”

Cognitive Sciences Applied to Social Media

A field that applies psychology, neuroscience, and cognitive anthropology to understand how social media affects attention, memory, decision‑making, and emotional regulation. It investigates phenomena like doomscrolling, addiction mechanics, echo chambers, and the cognitive load of managing multiple identities online. By treating the user as a cognitive agent, it reveals how platforms are designed to exploit vulnerabilities in human information processing—attention loops, confirmation bias, social validation—and how users can develop metacognitive strategies to resist manipulation.
Example: “Cognitive sciences applied to social media explained why outrage spreads faster than nuance: the brain’s negativity bias is amplified by algorithmic rewards, creating a feedback loop that shapes public discourse.”