International Conference on Weblogs and Social Media

Graph Mining Techniques for Social Media Analysis

author: Mary McGlohon, School of Computer Science, Carnegie Mellon University

Categories

Top: Computer Science: Network Analysis: Social Networks

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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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