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International Conference on Weblogs and Social Media

Graph Mining Techniques for Social Media Analysis

author: Mary McGlohon, School of Computer and Information Science, Carnegie Mellon University
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Slides
0:00 Graph Mining Techniques for Social Media Analysis
0:40 What is graph mining?
1:29 What is graph mining?
2:08 What is graph mining?
3:10 Motivating questions
3:51 Outline
5:02 Part 1 Outline
5:10 D1: Network
5:45 D2: Adjacency matrix
6:34 D3: Bipartite graphs
7:07 D4: Components
7:34 D4: Components
7:46 D5: Diameter
8:03 D5: Diameter
8:13 D5: Diameter
8:47 D6: Degree distribution
9:21 Some graphs
10:00 Part 1 Outline
10:21 Small-world effect
11:17 [Leskovec & Horvitz 07]
11:53 Part 1 Outline
12:03 Degree distribution
12:48 Degree distribution
13:23 Power law degree distribution
13:36 Power laws - discussion
13:45 Power laws - discussion
14:31 Time Evolution: rank R
14:37 The Peer-to-Peer Topology
14:54 epinions.com
15:00 Part 1 Outline
15:04 Components
15:40 Giant connected component
16:19 Part 1 Outline
16:39 Motivating questions
16:53 Evolution of diameter?
17:24 Shrinking diameter
18:08 Shrinking diameter
18:39 Shrinking diameter
19:02 Shrinking diameter
19:18 Temporal evolution
19:41 Temporal evolution
19:45 Temporal evolution
20:02 Densification Power Law
20:17 Densification Power Law
20:26 Densification Power Law
20:34 Densification Power Law
20:40 Densification Power Law
20:44 Densification Power Law
20:51 Part 1 Outline
21:14 Another big question
21:29 Another big question
21:45 Bibliography: Part 1
21:50 Bibliography: Part 1
21:51 Bibliography: Part 1
21:53 Bibliography: Part 1
21:54 Bibliography: Part 1
21:56 The End

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