博文
Adamic相关工作总结
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最近一段时间一直在整理与social network analysis and modeling，information diffusion相关的论文。虽然关于social media上的研究工作开展没几年，但是参与这方面研究的专家以及这方面的工作确实非常的多的，很多complex network方面的大牛也参合了进来，比如像Duncan Watts(Yahoo! Research), J.Kleinberg(Cornell Univ.), B.A.Huberman(HP lab), Albert L Barabasi(Northeastern Univ.), L.A.Adamic(Michigan Univ.) J.Leskovec(Stanford Univ.)等。这篇博文主要总结了一下近三年来L.A.Adamic关于social networks主要工作，主要集中在link prediction方向。
https://m.sciencenet.cn/blog-664193-518502.html
1) I rate you. You rate me. Should we do so publicly? (paper)
Are online social networks accurate?
OSNs是一个数据的宝库，社交网络的特性加强了某些功能（如推荐），如何获得真实的rating。
trust and friendship的量化问题
trust and friendship
truthful ratings reliable?
gender effect, age, geography
Conclusion: Rating friends is tricky,rating enimies is trickier.
2) Implicit Structure (link prediction)
Microscale Dynamics
What we need to track?
timings
underlying networks
Challenges
Root may be unknown
Multiple possible paths
Uncrawled space, alternate media (email, voice)
No links
3) Meme spread in networks
info changes as it propagates through a network
multi-step diffusion is responsible for change
the change can be model as a simple urn process
the characteristics of nodes and their position in the network correspond to different amount of change
4) Social networks influence and are influenced by information exchange
Computational social science can contribute to understanding of social phenomena
homophily
information diffusion
social influence
knowledge exchange
trust & reciprocity
其中，本人对其两个工作比较感兴趣。
一、different kinds of info popularity profiles （见Fig.1, Fig.2）
二、meme tracing （见Fig.3）
Fig.1 different kinds of info popularity profiles
Fig.2 different kinds of info popularity profiles
Fig.3 meme example
https://m.sciencenet.cn/blog-664193-518502.html
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