Graph Neural Networks and Applications Jie Tang Computer Science Tsinghua University The slides can be downloaded at http://keg.cs.tsinghuaeducn/jietang
1 Graph Neural Networks and Applications Jie Tang Computer Science Tsinghua University The slides can be downloaded at http://keg.cs.tsinghua.edu.cn/jietang
Networked world facebook Alibaba Group 里巴巴集团 ·2 billion mau >777 million trans. (alipay) 26.4 billion minutes/day ·200 billion on11/11 twitter 新浪微博 weibo. com 320 million mau ·462 million users ·Peak:143 K tweets/s influencing our daily life instagram 头系今日头条 700 million Mau 1.5 billion mau ·95 million pics/day 70 minutes/user/day snapchat ·300 million mau QQ 860 million mau ·30 minutes/use/day WeChat: 1.1 billion Mau
2 Networked World • 2 billion MAU • 26.4 billion minutes/day • 462 millionusers • influencing our daily life • 320 millionMAU • Peak: 143K tweets/s •QQ: 860 million MAU • WeChat: 1.1 billion MAU • 700 millionMAU • 95 million pics/day • >777 million trans. (alipay) • 200 billion on 11/11 • 300 millionMAU • 30 minutes/user/day • ~1.5 billion MAU • 70 minutes/user/day
Mining big Graphs/Networks An information/social graph is made up of a set of individuals/entities (nodes)tied by one or more interdependency (edges), such as friendship Mining big networkS: A field is emerging that leverages the capacity to collect and analyze data at a scale that may reveal patterns of individu and group behaviors.” 1. David Lazer, Alex Pentland, Lada Adamic, Sinan Aral, Alber-Laszlo Barabasi, et aL. Computational Social Science. Science 2009
3 Mining Big Graphs/Networks • An information/social graph is made up of a set of individuals/entities (“nodes”) tied by one or more interdependency (“edges”), such as friendship. 1. David Lazer, Alex Pentland, Lada Adamic, Sinan Aral, Alber-Laszlo Barabasi, et al. Computational Social Science. Science 2009. Mining big networks: “A field is emerging that leverages the capacity to collect and analyze data at a scale that may reveal patterns of individual and group behaviors.” [1]
Let us start with an example Social influence and prediction
4 Let us start with an example —Social influence and prediction
Social Influence: Love Trump Trump makes I hate Trump, the USa great again worst president ever Trump is fantastic Trump is great No Trump in 2020 He cannot be the next president O Positive ONe
5 Social Influence: “Love Trump” Trump makes USA great again Trump is great! Trump is fantastic I hate Trump, the worst president ever He cannot be the next president! No Trump in 2020! Positive Negative