Title
Groups without tears: mining social topologies from email
Abstract
As people accumulate hundreds of "friends" in social media, a flat list of connections becomes unmanageable. Interfaces agnostic to social structure hinder the nuanced sharing of personal data such as photos, status updates, news feeds, and comments. To address this problem, we propose social topologies, a set of potentially overlapping and nested social groups, that represent the structure and content of a person's social network as a first-class object. We contribute an algorithm for creating social topologies by mining communication history and identifying likely groups based on co-occurrence patterns. We use our algorithm to populate a browser interface that supports creation and editing of social groups via direct manipulation. A user study confirms that our approach models subjects' social topologies well, and that our interface enables intuitive browsing and management of a personal social landscape.
Year
DOI
Venue
2011
10.1145/1943403.1943417
IUI
Keywords
Field
DocType
social structure,social network,personal social landscape,personal data,social group,social media,browser interface,social topology,nested social group,approach models subject,social groups,access control
Social group,World Wide Web,Social network,Social media,Social graph,Social media optimization,Social web,Computer science,Human–computer interaction,Social computing,Social heuristics
Conference
Citations 
PageRank 
References 
24
1.17
16
Authors
5
Name
Order
Citations
PageRank
Diana Maclean11076.34
Sudheendra Hangal253635.73
Seng Keat Teh3241.17
Monica S. Lam45585705.61
Jeffrey Heer55322349.19