作者：Michel Plantie, Michel Crampes
年份：2013
期刊：Social media retrieval. Springer London
研究内容：对以往的Social Community Detection研究进行了总结，得出三种常见的分析方法。
- The first approach considers the social network as a graph and then analyzes its structure with graph properties and algorithms built around the graph structure.
- The second approach associates the social network with a hypergraph and analyzes its structure through hypergraph properties and algorithms based on hypergraph structures.
- The third approach uses the properties of concept lattices in order to analyze the social network structure in association with hypergraph properties and algorithms based on Galois lattices and hypergraph structures.
总结很详细，不过没读完。
¶关键对象说明
- 图(Graph)：node和edge构成，edge只连接两个nodes。
- 超图(Hypergraph)：node和hyperedges构成，hyperedges可以连接多个nodes，一个hyperedges内包含的就是一个community。
- Galois点阵（Galois lattice）Individuals sharing the same subset of properties define a community. row是属性，column是对象，画出一个图，包含先沟通的子集的对象被认为是一个community。
