Michael S Bernstein
Biographic Data
| ID | 308027 |
|---|---|
| NAME | Michael S Bernstein |
| GIVEN NAMES | Michael S |
| FAMILY NAME | Bernstein |
| SIGNATURE | BERNSTEIN M S |
| AFFILIATIONS | Stanford University |
| ORCID | 0000-0001-8020-9434 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 3 |
| AUTHOR COUNT | 5 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2015 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 1 |
Internal Fractures: The Competing Logics of Social Media Platforms
Social media platforms are too often understood as monoliths with clear priorities. Instead, we analyze them as complex organizations torn between starkly different justifications of their missions. Focusing on the case of Meta, we inductively analyze the company's public materials and identify three evaluative logics that shape the platform's decisions: an engagement logic, a public debate logic, and a wellbeing logic. There are clear trade-offs…
Generative Agents: Interactive Simulacra of Human Behavior
Believable proxies of human behavior can empower interactive applications ranging from immersive environments to rehearsal spaces for interpersonal communication to prototyping tools. In this paper, we introduce generative agents: computational software agents that simulate believable human behavior. Generative agents wake up, cook breakfast, and head to work; artists paint, while authors write; they form opinions, notice each other, and initiate…
Embedding Societal Values into Social Media Algorithms
Social media influences what we see and hear, what we believe, and how we act-but artificial intelligence (AI) influences social media.By changing our social environments, AIs change our social behavior: as per Winston Churchill, "We shape our buildings; thereafter, they shape us."Across billions of people on platforms from Facebook to Twitter to YouTube to TikTok, AI decides what is at the top of our feeds (Backstrom 2016; Fischer 2020), who we …
Better When It Was Smaller? Community Content and Behavior After Massive Growth
Online communities have a love-hate relationship with membership growth: new members bring fresh perspectives, but old-timers worry that growth interrupts the community’s social dynamic and lowers content quality. To arbitrate these two theories, we analyze over 45 million comments from 10 Reddit subcommunities following an exogenous shock when each subcommunity was added to the default set for all Reddit users. Capitalizing on these natural expe…
ImageNet Large Scale Visual Recognition Challenge
Internal Fractures: The Competing Logics of Social Media Platforms
Social media platforms are too often understood as monoliths with clear priorities. Instead, we analyze them as complex organizations torn between starkly different justifications of their missions. Focusing on the case of Meta, we inductively analyze the company's public materials and identify three evaluative logics that shape the platform's decisions: an engagement logic, a public debate logic, and a wellbeing logic. There are clear trade-offs…
Embedding Societal Values into Social Media Algorithms
Social media influences what we see and hear, what we believe, and how we act-but artificial intelligence (AI) influences social media.By changing our social environments, AIs change our social behavior: as per Winston Churchill, "We shape our buildings; thereafter, they shape us."Across billions of people on platforms from Facebook to Twitter to YouTube to TikTok, AI decides what is at the top of our feeds (Backstrom 2016; Fischer 2020), who we …
ImageNet Large Scale Visual Recognition Challenge
Better When It Was Smaller? Community Content and Behavior After Massive Growth
Online communities have a love-hate relationship with membership growth: new members bring fresh perspectives, but old-timers worry that growth interrupts the community’s social dynamic and lowers content quality. To arbitrate these two theories, we analyze over 45 million comments from 10 Reddit subcommunities following an exogenous shock when each subcommunity was added to the default set for all Reddit users. Capitalizing on these natural expe…
Generative Agents: Interactive Simulacra of Human Behavior
Believable proxies of human behavior can empower interactive applications ranging from immersive environments to rehearsal spaces for interpersonal communication to prototyping tools. In this paper, we introduce generative agents: computational software agents that simulate believable human behavior. Generative agents wake up, cook breakfast, and head to work; artists paint, while authors write; they form opinions, notice each other, and initiate…
Embedding Societal Values into Social Media Algorithms
Social media influences what we see and hear, what we believe, and how we act-but artificial intelligence (AI) influences social media.By changing our social environments, AIs change our social behavior: as per Winston Churchill, "We shape our buildings; thereafter, they shape us."Across billions of people on platforms from Facebook to Twitter to YouTube to TikTok, AI decides what is at the top of our feeds (Backstrom 2016; Fischer 2020), who we …
Internal Fractures: The Competing Logics of Social Media Platforms
Social media platforms are too often understood as monoliths with clear priorities. Instead, we analyze them as complex organizations torn between starkly different justifications of their missions. Focusing on the case of Meta, we inductively analyze the company's public materials and identify three evaluative logics that shape the platform's decisions: an engagement logic, a public debate logic, and a wellbeing logic. There are clear trade-offs…
Computer Science (5 works) · Artificial Intelligence (2 works) · Business (2 works) · Opinion Dynamics and Social Influence (2 works) · Social media (2 works) · Social Media and Politics (2 works) · World Wide Web (2 works) · 3D single-object recognition (1 works) · Advanced Image and Video Retrieval Techniques (1 works) · Advanced Neural Network Applications (1 works)