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» Social Network Data and Practices: The Case of Friendfeed
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CHI
2009
ACM
14 years 8 months ago
Predicting tie strength with social media
Social media treats all users the same: trusted friend or total stranger, with little or nothing in between. In reality, relationships fall everywhere along this spectrum, a topic...
Eric Gilbert, Karrie Karahalios
KDD
2009
ACM
179views Data Mining» more  KDD 2009»
14 years 2 months ago
Identifying graphs from noisy and incomplete data
There is a growing wealth of data describing networks of various types, including social networks, physical networks such as transportation or communication networks, and biologic...
Galileo Mark S. Namata Jr., Lise Getoor
WWW
2007
ACM
14 years 8 months ago
Finding community structure in mega-scale social networks: [extended abstract]
[Extended Abstract] Ken Wakita Tokyo Institute of Technology 2-12-1 Ookayama, Meguro-ku Tokyo 152-8552, Japan wakita@is.titech.ac.jp Toshiyuki Tsurumi Tokyo Institute of Technolog...
Ken Wakita, Toshiyuki Tsurumi
KDD
2008
ACM
164views Data Mining» more  KDD 2008»
14 years 8 months ago
Microscopic evolution of social networks
We present a detailed study of network evolution by analyzing four large online social networks with full temporal information about node and edge arrivals. For the first time at ...
Jure Leskovec, Lars Backstrom, Ravi Kumar, Andrew ...
DMS
2010
189views Multimedia» more  DMS 2010»
13 years 5 months ago
Visualizing the Commonalities Between Hierarchically Structured Data Queries
Abstract--In this paper we present an information visualization approach for visualizing the intersection between multiple feature hierarchies. In cases where a dataset has multipl...
Chad Jones, Ryan Armstrong, Kwan-Liu Ma