Virality and network effects are conflated by even experienced Founders, and it keeps them from developing the right strategies and playbooks.
Every layer of review makes you 10x slower
We’ve all heard of those network effect laws: the value of a network goes up with the square of the number of members. Or the cost of commun...
The Dark Forest Theory of the Internet
Why the dark forests of the internet — podcasts, newsletters, and other private channels — are growing, and why might that pose a problem
One Response to the Cambridge Analytica Scandal: Block Facebook's
With Facebook in a dominant position in hosting a huge portion of the world’s social conversation, we’ve been worried about the incredible power the company has accumulated and the risks that poses
Estimating the effect size of moral contagion in online networks: A pre-registered replication and meta-analysis
Abstract. Over 5 billion people now use social media platforms. As our social lives become increasingly entangled with online social networks, it is import
Marc Andreessen as Avatar for Societal Decay
How one venture capitalist represents everything wrong with social media
Media and Social Capital
We survey the empirical literature in economics on the impact of media technologies on social capital. Guided by a simple model of information and collective action, we cover a range of different outcomes related to social capital—from social and political participation to interpersonal trust—in its benign and destructive manifestations. The impact of media technologies hinges on their content (information versus entertainment), their effectiveness in fostering coordination, and the networks they create as well as on individual characteristics and media consumption choices.
Fake news spreads like an epidemic. Here’s how to stop it.
Researchers study fake news the same way they study the spread of disease. When misinformation “goes viral”, it is not just a metaphor. It is what’s actually happening. via @straits_times str.sg/viz-misinformation
Do Science <i>Kardashians</i> Get Citation Premium? Self‐Fulfilling Effects of Social Media on Scientific Impact
ABSTRACT We analyze whether the visibility of scientists on social media affects the number of academic citations. We use the global COVID‐19 pandemic as a quasinatural experiment that exogenously increased public attention and the demand for expertise. Using publications on COVID‐related topics by social media stars and their coauthors prior to the outbreak of the pandemic, we find that social media stars' pre‐COVID‐era papers received about – more citations annually per paper after 2019. Quantitatively comparable results are obtained when we use scientists' Kardashian index (K‐index) as a benchmark for stardom, however we find no significant effects when using the intensive margin of scientists' K‐indexes. We provide a brief discussion of policy implications in light of these findings.
The Majority Illusion in Social Networks
Social behaviors are often contagious, spreading through a population as individuals imitate the decisions and choices of others. A variety of global phenomena, from innovation adoption to the emergence of social norms and political movements, arise as a result of people following a simple local rule, such as copy what others are doing. However, individuals often lack global knowledge of the behaviors of others and must estimate them from the observations of their friends' behaviors. In some cases, the structure of the underlying social network can dramatically skew an individual's local observations, making a behavior appear far more common locally than it is globally. We trace the origins of this phenomenon, which we call "the majority illusion," to the friendship paradox in social networks. As a result of this paradox, a behavior that is globally rare may be systematically overrepresented in the local neighborhoods of many people, i.e., among their friends. Thus, the "majority illusion" may facilitate the spread of social contagions in networks and also explain why systematic biases in social perceptions, for example, of risky behavior, arise. Using synthetic and real-world networks, we explore how the "majority illusion" depends on network structure and develop a statistical model to calculate its magnitude in a network.
The "Majority Illusion" in Social Networks
Individual’s decisions, from what product to buy to whether to engage in risky behavior, often depend on the choices, behaviors, or states of other people. People, however, rarely have global knowledge of the states of others, but must estimate them from the local observations of their social contacts. Network structure can significantly distort individual’s local observations. Under some conditions, a state that is globally rare in a network may be dramatically over-represented in the local neighborhoods of many individuals. This effect, which we call the “majority illusion,” leads individuals to systematically overestimate the prevalence of that state, which may accelerate the spread of social contagions. We develop a statistical model that quantifies this effect and validate it with measurements in synthetic and real-world networks. We show that the illusion is exacerbated in networks with a heterogeneous degree distribution and disassortative structure.
The "Majority Illusion" in Social Networks
Individual’s decisions, from what product to buy to whether to engage in risky behavior, often depend on the choices, behaviors, or states of other people. People, however, rarely have global knowledge of the states of others, but must estimate them from the local observations of their social contacts. Network structure can significantly distort individual’s local observations. Under some conditions, a state that is globally rare in a network may be dramatically over-represented in the local neighborhoods of many individuals. This effect, which we call the “majority illusion,” leads individuals to systematically overestimate the prevalence of that state, which may accelerate the spread of social contagions. We develop a statistical model that quantifies this effect and validate it with measurements in synthetic and real-world networks. We show that the illusion is exacerbated in networks with a heterogeneous degree distribution and disassortative structure.
The Dimensions of Emergent Spacetime in the Influence Network
The Dimensions of Emergent Spacetime in the Influence Network KEVIN KNUTH, State Univ of NY -Albany -It has been previously demonstrated that the consistent quantification of a causally ordered set of events (influence network) with respect to
This started up as a write-up for a cool hack I made (Atproto DID + Tailscale, coming soon 😎), but like many times before it started taking a life of its own, about how an integration of small scale networks is a more sustainable version of "internet scale" than large tech monopoly data centers.
Increasing lot sizes of our digital homes
thinking-with-portals.leaflet.pubOne of the issues that has come up again and again in my reporting on misinformation and social media is the massive influence social media companies have on research in the field. Last night a preprint dropped that tries to get at this with some numbers. My piece in @science.org (and 🧪🧵 coming):
Nearly a third of social media research has undisclosed ties to industry, preprint claims
www.science.orgIt's important to understand: social networks are not meant to be one-size-fits all! When Meta (which makes Threads, as well as Facebook and Instagram) creates platforms that have hundreds of millions of users, they do things like enable genocides, where tens of thousands of innocent people die.
Christopher Mims
So I guess either Bluesky becomes a nonprofit or we all start sharing our Threads handles on here…?
