Subject
12 entries
Social Networks
Bookmarks
And You Will Know Us by the Company We Keep
Eugene Wei analyzes how your social circle functions as a status signal and how social networks exploit this — the people around you communicate who you are before you say a word. Sharp thinking on why social product design is fundamentally about group dynamics, not individual features.
Mapping Twitter Topic Networks: From Polarized Crowds to Community Clusters
Pew Research Center's 2014 network analysis of Twitter conversations — classifying discussion patterns into six archetypes (polarized crowds, tight crowds, brand clusters, community clusters, broadcast networks, support networks). A rigorous look at how online discourse actually structures itself.
How the NSA Analyzes Call Metadata
GigaOm's technical explanation of how the NSA processes bulk call metadata — published in June 2013 immediately after the Snowden revelations. The article explains the graph analysis techniques that make even metadata (not call content) a powerful surveillance tool.
MIT Can Predict How Many Retweets You'll Get
Wired's coverage of MIT research predicting retweet counts from tweet content and network features. An early demonstration that social network propagation could be modeled predictively, with implications for understanding how information spreads.
Correlations with Tweet Density
Eric Fischer's Flickr set showing correlations between tweet density and other geographic variables across cities. Part of Fischer's influential 'Geotaggers' World Atlas' series exploring what social media geotag data reveals about urban activity and inequality.
You Are More Influential Than You Think You Are
Jay Shah's post on Facebook's finding that ordinary users have larger social influence than they think — driven by the long tail of weak-tie connections that Facebook's social graph captured better than individuals' self-perception.
Twitter Powers of Ten
Rob Weir's 2011 post using powers-of-ten framing to characterize Twitter's data and scale properties — from individual tweets to the full firehose. A snapshot of the social media scale conversation before big data tooling became mainstream.
Data Science of the Facebook World
Stephen Wolfram's data science analysis of Facebook social graph patterns — age cohort differences in network structure, relationship status effects, and how Wolfram Language's data computation tools enable individual-level analysis of social network data. A 2013 example of using data for personal-scale social science.
Sarkar — Graph Processing Paper (CMU AutonLab)
Prithwish Sarkar's paper from CMU's AutonLab on large-scale graph analysis — bookmarked alongside Apache Giraph as a reference for distributed graph processing. CMU's AutonLab works on scalable machine learning for graph-structured data.
Social Machine Learning — Cambridge Computer Lab Slides
Slides from a Cambridge Computer Lab course on social machine learning — applying ML to social network data, link prediction, community detection, and behavior modeling. A 2010-era academic reference captured at the boundary between network science and machine learning.
The Chart That Scared Zuckerberg Into Spending $1 Billion On Instagram
Business Insider's reporting on the internal mobile growth data that motivated Facebook's $1B Instagram acquisition — Instagram was growing faster on mobile than Facebook itself. A concrete case study in defensive acquisition driven by internal metrics.
Small By Design: Path, Familyleaf, and Pair
NYT's coverage of small-by-design social networks like Path, Familyleaf, and Pair in 2012 — products deliberately capping user counts to reflect cognitive limits on meaningful relationships. A reaction to Facebook's ambient mass-friend model.