阅读笔记:Social Graph: Concepts and Issues

Social Graph: Concepts and Issues:

Key Elements In Digital Social Graphs

With the recent rise and proliferation of social networks, the social graph comes into the spotlight. Unlike the one that scientists have been studying, this one is digital and defined explicitly by connections in all social networks. Let's revisit the main issues that Brad and others have been talking about:

1. People Identity Each one of us participates in multiple networks, but we want to be identified as the same person in all of them. Brad describes this as a multiple login nightmare. He calls for having a way to map IDs onto each other, via Node Equivalence:

"Given a single node, say "brad on LiveJournal", return all equivalent nodes: "brad" on LiveJournal, "bradfitz" on Vox, and 4caa1d6f6203d21705a00a7aca86203e82a9cf7a (my FOAF mbox_sha1sum)."

思考:OpenID是一种解决办法.但是国内信任危机的情况下,OpenID的出路在哪里?

2. Type of Relationships The links between people in social networks are of different types. Crudely, different types of relationships are a friend, a co-worker, a family member. There are more fine grained relationships defined in Facebook (see picture above) and Spock, which uses tags to identify how people are related.

思考:关系的类型.Tag当然有效.但问题是,如果跨网络的话,不同站点中间的Tag如何对接?甚至考虑不同站点可能对于同样的关系采用近似的Tag,但不是相同的tag,那时候谁按照谁的标准来统一呢?

3. Relationships Identity Similar to having node equivalence, there is an issue of edge equivalence. Although, this issue is more complicated. If two people are connected in one social network, should they automatically be connected in all of them? Consider an example of a LinkedIn and Shelfari. Just because two people work together does not mean that they share the same book interests. However, the crux of the issue is not that - it is actually discoverability. As Brad pointed out, there needs to be a way for a new user who joins a network to be able to find friends who are already using that network.

思考:这是目前各个SNS站上可能都比较弱的地方.关系的标识和识别.每个人都处在不同纬度的多个关系中,那么要不要把所有的关系自动关联合发现给用户呢?其中多少有意义?比如,虽然同在一间公司上班,但不意味着你们喜欢同一本书.而在兴趣方面,又的确有部分是相关的.在工作领域,也有部分是相关的.这种依据不同关系类型和场景的背后的关系发现可能是未来的比拼点.