Sam Liebeskind
@samliebeskind
product strategy at New_Public; previously community & growth @ Geneva
Sam Liebeskind
The core conceptual questions at the heart of my work are: “How do we equip people to become architects of their own future? How do people do that individually? And then how do people come together to forge a common life in which we can all realize a shared vision of the world that we want?” That's what drew me into studying politics: it’s the... See more
By continuing to pursue these lines of thought, we develop new ways of framing our interactions with the dead online, and may find pathways for breaking our calcified archival imaginaries and reimagine new ways of living with the data bodies we construct, inhabit, and inherit.
Sarah Wambold & Rem Moore: Only Loss
The simplest way to tell the story of my life is as an ongoing formation through a series of very muscular institutions: family, the Church, an all-boys Catholic school, the Marine Corps, Little League, and my local Fire Department. Each of these institutions had strong norms that facilitated connecting across difference—and, in practice, each of... See more
Jason Mangone • The paradox of “muscular institutions”
polarization vs coexistence & cohesion and
There is widespread concern about the negative impacts of social media feed ranking algorithms on political polarization. Leveraging advancements in large language models (LLMs), we develop an approach to re-rank feeds in real-time to test the effects of content that is likely to polarize: expressions of antidemocratic attitudes and partisan animosity (AAPA). In a preregistered 10-day field exper- iment on X/Twitter with 1,256 consented participants, we increase or decrease participants’ exposure to AAPA in their algorithmically curated feeds. We observe more positive outparty feelings when AAPA exposure is decreased and more neg- ative outparty feelings when AAPA exposure is increased. Exposure to AAPA content also results in an immediate increase in negative emotions, such as sadness and anger. The interventions do not significantly impact traditional engagement metrics such as re-post and favorite rates. These findings highlight a potential pathway for developing feed algorithms that mitigate affective polarization by addressing content that undermines the shared values required for a healthy democracy
