Data Science for Social Influence

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Nicholas Lincoln

9:50:16

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1 - Introduction

1 - About this Course.mp4

04:31

2 - Are You Ready for this Course.mp4

02:40

3 - Course Materials.html

2 - Psychology of Social Influence

4 - Psychology of Social Influence Intro.mp4

00:07

5 - A Perspective of Social Influence.mp4

13:48

6 - Cognitive Biases Part 1 Primers Illusory Truth Effect Availability Heuristic.mp4

08:03

7 - Cognitive Biases Part 2 Cognitive Dissonance.mp4

15:47

8 - Cognitive Biases Part 3 Conformity Ostracism.mp4

17:40

9 - Behavior in Groups.mp4

13:21

3 - Influence in Social Networks

10 - Influence in Social Networks Intro.mp4

01:58

11 - Influence.mp4

08:00

12 - Influence Decay and the Network Horizon.mp4

04:06

13 - Information Spread in Social Networks.mp4

11:26

14 - Phase Transitions in the Ising Model.mp4

31:05

15 - The Rise of an Influencer Demo of Detecting a Rising Star.mp4

18:51

4 - Graph Representation Learning

16 - Graph Representation Learning Intro.mp4

04:48

17 - Graph Feature Engineering.mp4

05:39

18 - Graph Spectral Properties the Laplacian.mp4

19:39

19 - Graph Embeddings.mp4

31:19

20 - GNNs Part 1.mp4

22:28

21 - GNNs Part 2.mp4

26:39

22 - Graph Convolutions GCNs.mp4

13:19

23 - Graph Embeddings GNNs for Dynamic Graphs.mp4

01:13

24 - Evaluating Graph Representations.mp4

12:11

25 - Project Overview Node Classification with GNNs.mp4

02:09

26 - Project Node Classification with GNNs.mp4

18:59

5 - Data Manipulation

27 - Data Manipulation Intro.mp4

00:57

28 - How to Fake Statistical Analysis.mp4

37:16

29 - Bayesian AB Testing.mp4

25:44

30 - How to Generate Realistic Data.mp4

00:51

31 - Demo How to Break Benfords Law.mp4

02:50

32 - Fake News Deepfakes.mp4

10:00

33 - How to Create a Deepfake Leverage it for Social Influence.mp4

15:28

34 - Exploiting Data Visualization.mp4

07:22

6 - Media Bias Propaganda

35 - Media Bias Propaganda Intro.mp4

00:23

36 - Media Bias.mp4

13:41

37 - Propaganda.mp4

10:13

38 - Censorship.mp4

05:11

39 - Project Overview Hate Speech Detection.mp4

03:07

40 - Project Hate Speech Detector.mp4

26:26

41 - Project Overview News Recommender.mp4

05:13

42 - Project News Recommender.mp4

37:01

7 - Directed Influence Campaigns Botnets

43 - Directed Influence Campaigns Intro.mp4

00:36

44 - Directed Influence.mp4

07:35

45 - Demo Social Botnet Detection.mp4

29:34

46 - Project Overview Directed Influence Campaign.mp4

03:05

47 - Project Directed Influence Campaign.mp4

37:57

8 - Conclusion

48 - Where to Go From Here.html

Description

Combining data, AI, network science, and psychology for social influence.

What You'll Learn?

How cognitive biases mold our view of the world, and how they can be leveraged to exert influence
How directed influence campaigns shape opinion in social networks
How AI can generate realistic data, and how that data can be used to deceive
How to build graph neural networks (GNN, GCN, GAT, Node2Vec, DeepWalk, & more)
How statistical analysis and hypothesis tests can be fudged to accept or reject any hypothesis
How to detect rising stars in social networks and root out botnets
Build a hate speech detector bot for Slack
Build a news recommendation website
Run Bayesian A/B tests in real time on your news recommendation website

Who is this for?

Data Scientists, ML Engineers, and Data Analysts with a few years of work experience or higher education

This is not a course for beginners.

More details

Description
A new age has arrived.Â AI is sufficiently advanced to learn our opinions and what we care about, and craft text and media to influence our thoughts and opinions.Â It is likely that AI will soon be better able to influence us than other people.Â Individuals and organizations equipped with AI are now able to exert influence at a previously inconceivable scale, and they will become more successful at it over time.
In this course, we will combine concepts from psychology, data science, and network science to describe how social influence can be exerted.Â We will consider how our thoughts are influenced by our social networks, and how our biases work.Â We will explore how an individualâ€™s opinions impact social networks, and how the collective opinions of entire networks can change under the right conditions.Â You will see how statistical analysis can be manipulated and how AI can be used for deception.Â Ultimately, you will learn how to exert large scale social influence, using AI for leverage.
This is not a course for beginners.Â Basic concepts in data science will not be explained.Â This is an interdisciplinary course that will challenge you to think for yourself.Â You will learn about powerful techniques and you will need to decide how to manage them ethically and morally.Â
Who this course is for:
Data Scientists, ML Engineers, and Data Analysts with a few years of work experience or higher education
This is not a course for beginners.

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Data Scientist and Consultant who holds patents in artificial intelligence (AI) and network science technologies. Has published research in The ITEA Journal of Test and Evaluation, and has published books on data science that teach statistics, machine learning, and AI. Specializes in developing AI applications following Agile and DevOps methodologies. Has an MS in Data Analytics.

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