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Social Media Analytics
Published on Sep 09, 201151980 Views
Online social media represent a fundamental shift of how information is being produced, transferred and consumed. The present tutorial investigates techniques for social media modeling, analytics and
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Chapter list
Social Media Analytics: Part 1: Information flow00:00
Information and Networks01:35
Social Media: Big change02:37
Social Media: Opportunities03:37
Social Media: Value proposition04:01
Applications: Reputation management04:28
Applications: Citizen response05:30
Applications: Real-time citizen journalism06:37
Applications: Social media marketing07:12
Applications: Human behaviour analysis07:57
The tutorial: Social Media08:34
Tutorial Outline (1)09:33
Part 1 of the Tutorial: Overview09:59
Social Media Data: Spinn3r10:35
Tracing Information Flow12:00
Tracing information (1): Hyperlinks14:02
Cascading hyperlinks14:45
Cascade Shapes15:51
Tracing sentiment of cascade (1)16:59
Tracing sentiment of cascade (2)18:20
Tracing hyperlinks: Pros/Cons20:55
Issue: Cascades and Missing data22:59
What happens with missing data?23:51
Problem Statement25:24
Tracing Information (2): Twitter25:59
Tracing Information on Twitter (1)26:42
Tracing Information on Twitter (2)28:37
Tracing Information on Twitter (3)29:46
Tracing Information (3): Memes30:44
Challenge: Quotes Mutate32:15
Finding Mutational Variants (1)33:37
Finding Mutational Variants (2)35:33
Insights: Quotes reveal pulse of media36:45
Insights: When sites mention quotes?37:38
Insights: Quotes on Great depression38:28
Tracing Information40:26
Tutorial Outline (2)41:10
Patterns of Information Attention41:27
Discovering Attention Patterns42:29
Clustering Temporal Signatures42:57
Patterns of Attention44:20
Analysis of Attention Patterns (1)46:00
Analysis of Attention Patterns (2)47:09
Predicting Information Attention (1)47:39
Predicting Information Attention (2)49:08
Linear Influence Model50:32
LIM: Strategy51:19
The Linear Influence Model (1)52:43
The Linear Influence Model (2)53:30
Estimating Influence Functions (1)55:03
LIM: Influence Functions55:33
LIM as Matrix Equation56:42
Estimating Influence Functions (2)57:45
LIM: Performance58:07
Analysis of Influence Functions01:01:44
Analysis of Influence01:02:40
Tutorial Outline (3)01:04:03
Inferring the Diffusion Network01:04:13
Inferring the Diffusion Networks01:04:50
Examples and Applications01:05:41
The optimization problem01:06:34
Information Diffusion Model (1)01:09:07
Information Diffusion Model (2)01:10:25
Complication: Too many trees01:11:57
Optimization problem01:13:09
NetInf: Submodularity01:15:19
NetInf: The Algorithm01:17:07
Experiments: Synthetic Data01:18:07
Example: Real Data01:19:07
Example: Diffusion Network01:19:46
Diffusion Network (small part)01:20:02
Detecting information outbreaks01:21:43
Two parts to the problem01:23:03
CELF: Covering stories01:24:07
Blogs: Information Epidemics01:24:33
Experimental Results01:25:29
Conclusions and Connections01:26:27
Further Qs: Opinion Dynamics01:27:12
References (1)01:27:37
References (2)01:27:45