Episodes:

Below is a list of lecture slide sets interspersed with video of each episode. Slides will become available as the semester progresses.

Slide sets are often spread over several episodes so below you will find separate, interconnected episode and slide lists.

All lectures are necessarily bottle episodes; we will occasionally overlay some other tropes.

The slides are clickable pdf's, with links to relevant articles and web pages, section links in the sidebar, and navigation icons at the bottom of each slide. The reference section for each set of slides includes links to papers; superscript citation numbers link to the reference section as well (please let me know if any links or penguins behave badly).

Due to remorseless tinkering, the slides may change a little from what was recorded. Some video details:

  1. Screen capture and video creation is made possible by ScreenFlow.
  2. Implements include several iPod touches, the Swivl thing, Contour Roam2, Sennheiser wireless kit, and a Countryman microphone.
  3. Slides will generally be viewable in HD (720p).
  4. The youtube playlist for all videos is here.
  5. No comfy chairs will be used.

To generate these lectures, I use the excellent beamer LaTeX class, XeLaTeX (new this season), PerlTeX, and a selection of handcrafted, possibly dangerous Perl scripts. Because It Is Right, I follow the one true path of Emacs with an almost fanatical devotion.

Each set of slides comes in three delicious flavors:
  • The slides pdf's have flattened frames and are better for reading separately online. Use these if you follow the (terrifyingly long) videos and want to click on things.
  • If you want a printed copy, because trees upset you, the handout pdf's provide condensed and collapsed versions of the slides. These aren't very hyperlinky however (such is paper).

Episode Guide:

S7E01: Introduction to Monologuing.
('Tis a remorseless talking machine.)

S7E02: The Complexity Manifesto.
And a start on power-law size distributions.

S7E03: More on Power-Law Size Distributions and Zipf's law.
Bonus: Don Bradman and some Zipfian analyses.

S7E04: Fundmamentals: Emergence.
And some guff about projects.

S7E05: Elementary explanations for power-law size distributions: Random Walks and the Problem of First Return.
Also: Randomness of Stock Markets and Plinko.

S7E06: Elementary explanations for power-law size distributions: Variable transformation.
Also: The Evilness of PLIPLO.

S7E07: Simon's Rich-Get-Richer Model.
In the beginning there was the word, and that word was "Ook". Also: elephants.

S7E08: The Quickening—Benoit Mandelbrot takes on Herbert Simon with optimization-fu.
Or: "My Theory is much better than yours will ever be".

S7E09: The conclusion to epic battle between Simon and Mandelbrot.
Also: Benford's Law, Statistical Mechanics, and how cats lap. #realScience

S7E10: Robustness and Fragility of Complex Systems: Highly Optimized Tolerance.
Included: the examplar models provided by the Death Star and the Emperor's psychological wellbeing.

S7E11: More on robustness, self-organized criticality, highly suspicious heavy tailed size distributions and associated mechanisms, and a start on complex networks.
How some things fall apart.

S7E12: Overview of Complex Networks.
It is on, very much in the manner of Donkey Kong.

S7E13: Properties of Complex Networks.
What really matters if we care about reality (and we do because we're scientists).

S7E14: Models of Complex Networks.
Generalized Random Networks and Small-World Networks (Act 1):

S7E15: Small-World Networks (Act 2).
Theory (no rest for the).

S7E16: More on Small-World Network Theory (Act 3) and a start on Scale-Free Networks (Act 1).
Mechanisms, Universality, and Tricksiness.

S7E17: Scale-Free Networks (Act 2).
Theory bonanza.

S7E18: Finish of Scale-Free Networks (Act 3); Introduction to Contagion.
Boo! It's Halloween ...

S7E19: Plague prediction and introduction to social contagion (52:00).
Do you know who your friends have been copying?

S7E20: Methods for extracting phrases from natural language, implications for Zipf's law, and more.
Lecture given by Special Guest Star PhD student Jake Williams.

S7E21: Social contagion.
More overview and simple mean-field models.

S7E22: Social contagion.
Network models.

S7E23: Social contagion on group-based networks and intro to Superstardom.
Fame.

S7E24: How to become famous.
And a small, brave foray into allometric scaling.

S7E25: The Theory of Anything, Universality and Chance, Complexification, and Stories.
Prefaced with a little more about scaling.


Slide Guide:

01. Overview of complex systems

02. Power-law size distributions

03. A touch of Zipf.
Measure All The Things.

04. Suggestions for projects.

05. Mechanisms leading to power-law size distributions: Part 1.
Randomness. We explore the Snormals.

06. Mechanisms leading to power-law size distributions: Part 2.
Herbert Simon's and Benoît Mandelbrot's ideas about each other's ideas.

07. Benford's law.

08. Robustness, Fragility, and Scaling.

09. Lognormals and other impediments to universality.
Things get complicated.

10. Overview of complex networks.
On the underlying fabric of many complex systems, with a survey of network properties that matter.

11. Core models of complex networks.
Covers Generalized Random Networks, Small-World Networks, and Scale-Free Networks.

12. Contagion-at-large and biological contagion.
(Cue Zombies.)

13. Social contagion.
Insights into how things spread.

14. Voting and superstardom.
Why things take off.

15. Contagious stories
Homo narrativus and fame.

16. Allometric Scaling.
All about shapes and sizes.

17. Complexification.
The Arrow of Complexity, and the Big Transitions.

18. Bibliography.
All references for the course.


Episodes:

Episode 01: Introduction to Monologuing.
('Tis a remorseless talking machine.)


Slides covered:
01. Overview of complex systems

Episode 02: The Complexity Manifesto.
And a start on power-law size distributions.


Slides covered:
01. Overview of complex systems
02. Power-law size distributions

Episode 03: More on Power-Law Size Distributions and Zipf's law.
Bonus: Don Bradman and some Zipfian analyses.

Note: Quality fail by ScreenFlow and Swivl. Curses.

Slides covered:
02. Power-law size distributions
01. Overview of complex systems

Episode 04: Fundmamentals: Emergence.
And some guff about projects.


Slides covered:
01. Overview of complex systems
01. Overview of complex systems

Episode 05: Elementary explanations for power-law size distributions: Random Walks and the Problem of First Return.
Also: Randomness of Stock Markets and Plinko.

Online only!

Slides covered:
05. Mechanisms leading to power-law size distributions: Part 1.

Episode 06: Elementary explanations for power-law size distributions: Variable transformation.
Also: The Evilness of PLIPLO.


Slides covered:
05. Mechanisms leading to power-law size distributions: Part 1.

Episode 07: Simon's Rich-Get-Richer Model.
In the beginning there was the word, and that word was "Ook". Also: elephants.


Slides covered:
06. Mechanisms leading to power-law size distributions: Part 2.

Episode 08: The Quickening—Benoit Mandelbrot takes on Herbert Simon with optimization-fu.
Or: "My Theory is much better than yours will ever be".

Deeply related: see Colbert punditry-based Quickening here and here.

Slides covered:
06. Mechanisms leading to power-law size distributions: Part 2.

Episode 09: The conclusion to epic battle between Simon and Mandelbrot.
Also: Benford's Law, Statistical Mechanics, and how cats lap. #realScience


Slides covered:
06. Mechanisms leading to power-law size distributions: Part 2.
07. Benford's law.
01. Overview of complex systems

Episode 10: Robustness and Fragility of Complex Systems: Highly Optimized Tolerance.
Included: the examplar models provided by the Death Star and the Emperor's psychological wellbeing.


Slides covered:
08. Robustness, Fragility, and Scaling.

Episode 11: More on robustness, self-organized criticality, highly suspicious heavy tailed size distributions and associated mechanisms, and a start on complex networks.
How some things fall apart.


Slides covered:
08. Robustness, Fragility, and Scaling.
09. Lognormals and other impediments to universality.
10. Overview of complex networks.

Episode 12: Overview of Complex Networks.
It is on, very much in the manner of Donkey Kong.


Slides covered:
10. Overview of complex networks.

Episode 13: Properties of Complex Networks.
What really matters if we care about reality (and we do because we're scientists).


Slides covered:
10. Overview of complex networks.

Episode 14: Models of Complex Networks.
Generalized Random Networks and Small-World Networks (Act 1):

Note: Hershlag = Portman.

Slides covered:
11. Core models of complex networks.

Episode 15: Small-World Networks (Act 2).
Theory (no rest for the).


Slides covered:
11. Core models of complex networks.

Episode 16: More on Small-World Network Theory (Act 3) and a start on Scale-Free Networks (Act 1).
Mechanisms, Universality, and Tricksiness.


Slides covered:
11. Core models of complex networks.

Episode 17: Scale-Free Networks (Act 2).
Theory bonanza.


Slides covered:
11. Core models of complex networks.

Episode 18: Finish of Scale-Free Networks (Act 3); Introduction to Contagion.
Boo! It's Halloween ...


Slides covered:
11. Core models of complex networks.
12. Contagion-at-large and biological contagion.

Episode 19: Plague prediction and introduction to social contagion (52:00).
Do you know who your friends have been copying?


Slides covered:
12. Contagion-at-large and biological contagion.
13. Social contagion.

Episode 20: Methods for extracting phrases from natural language, implications for Zipf's law, and more.
Lecture given by Special Guest Star PhD student Jake Williams.

No video, slides are here.


Episode 21: Social contagion.
More overview and simple mean-field models.


Slides covered:
13. Social contagion.

Episode 22: Social contagion.
Network models.


Slides covered:
13. Social contagion.

Episode 23: Social contagion on group-based networks and intro to Superstardom.
Fame.


Slides covered:
13. Social contagion.
14. Voting and superstardom.

Episode 24: How to become famous.
And a small, brave foray into allometric scaling.


Slides covered:
15. Contagious stories
16. Allometric Scaling.

Episode 25: The Theory of Anything, Universality and Chance, Complexification, and Stories.
Prefaced with a little more about scaling.


Slides covered:
16. Allometric Scaling.
17. Complexification.

Slides:

01. Overview of complex systems
[slides]     [handout]     [lecture]
       
Covered in the following episode:
S7E01: Introduction to Monologuing.
S7E02: The Complexity Manifesto.
S7E04: Fundmamentals: Emergence.
S7E09: The conclusion to epic battle between Simon and Mandelbrot.

02. Power-law size distributions
[slides]     [handout]     [lecture]
       
Covered in the following episode:
S7E02: The Complexity Manifesto.
S7E03: More on Power-Law Size Distributions and Zipf's law.

03. A touch of Zipf.
[slides]     [handout]     [lecture]
       
Covered in the following episodes:
S7E03: More on Power-Law Size Distributions and Zipf's law.

04. Suggestions for projects.
[slides]     [handout]     [lecture]
       
Covered in the following episodes:
S7E04: Fundmamentals: Emergence.

05. Mechanisms leading to power-law size distributions: Part 1.
[slides]     [handout]     [lecture]
       
Covered in the following episode:
S7E05: Elementary explanations for power-law size distributions: Random Walks and the Problem of First Return.
S7E06: Elementary explanations for power-law size distributions: Variable transformation.

06. Mechanisms leading to power-law size distributions: Part 2.
[slides]     [handout]     [lecture]
       
Covered in the following episode:
S7E07: Simon's Rich-Get-Richer Model.
S7E08: The Quickening—Benoit Mandelbrot takes on Herbert Simon with optimization-fu.
S7E09: The conclusion to epic battle between Simon and Mandelbrot.

07. Benford's law.
[slides]     [handout]     [lecture]
       
Covered in the following episodes:
S7E09: The conclusion to epic battle between Simon and Mandelbrot.

08. Robustness, Fragility, and Scaling.
[slides]     [handout]     [lecture]
       
Covered in the following episode:
S7E10: Robustness and Fragility of Complex Systems: Highly Optimized Tolerance.
S7E11: More on robustness, self-organized criticality, highly suspicious heavy tailed size distributions and associated mechanisms, and a start on complex networks.

09. Lognormals and other impediments to universality.
[slides]     [handout]     [lecture]
       
Covered in the following episodes:
S7E11: More on robustness, self-organized criticality, highly suspicious heavy tailed size distributions and associated mechanisms, and a start on complex networks.

10. Overview of complex networks.
[slides]     [handout]     [lecture]
       
Covered in the following episode:
S7E12: Overview of Complex Networks.
S7E13: Properties of Complex Networks.

11. Core models of complex networks.
[slides]     [handout]     [lecture]
       
Covered in the following episode:
S7E14: Models of Complex Networks.
S7E15: Small-World Networks (Act 2).
S7E16: More on Small-World Network Theory (Act 3) and a start on Scale-Free Networks (Act 1).
S7E17: Scale-Free Networks (Act 2).
S7E18: Finish of Scale-Free Networks (Act 3); Introduction to Contagion.

12. Contagion-at-large and biological contagion.
[slides]     [handout]     [lecture]
       
Covered in the following episode:
S7E18: Finish of Scale-Free Networks (Act 3); Introduction to Contagion.
S7E19: Plague prediction and introduction to social contagion (52:00).

13. Social contagion.
[slides]     [handout]     [lecture]
       
Covered in the following episode:
S7E19: Plague prediction and introduction to social contagion (52:00).
S7E21: Social contagion.
S7E22: Social contagion.
S7E23: Social contagion on group-based networks and intro to Superstardom.

14. Voting and superstardom.
[slides]     [handout]     [lecture]
       
Covered in the following episodes:
S7E23: Social contagion on group-based networks and intro to Superstardom.

15. Contagious stories
[slides]     [handout]     [lecture]
       
Covered in the following episodes:
S7E24: How to become famous.

16. Allometric Scaling.
[slides]     [handout]     [lecture]
       
Covered in the following episode:
S7E24: How to become famous.
S7E25: The Theory of Anything, Universality and Chance, Complexification, and Stories.

17. Complexification.
[slides]     [handout]     [lecture]
       
Covered in the following episodes:
S7E25: The Theory of Anything, Universality and Chance, Complexification, and Stories.

18. Bibliography.
[slides]     [handout]     [lecture]
       

Additional topics and extra lectures:

  1. Language evolution:
    [slides]     [handout]     [lecture]
           


  2. Sociotechnical Phenomena—computation and algorithms:
    [slides]     [handout] [lecture]

  3. Personality distributions:
    [slides] [handout] [lecture]

  4. Shocks and Memory:
    [slides] [handout] [lecture]

  5. Cooperation:
    [slides] [handout] [lecture]

  6. Prediction:
    [slides] [handout] [lecture]

  7. Collective Intelligence:
    [slides] [handout] [lecture]

  8. Cities:
    [slides] [handout] [lecture]

  9. Entropy:
    [slides] [handout] [lecture]

  10. Information theory:
    [slides] [handout] [lecture]

  11. Generalized contagion:
    [slides] [handout] [lecture]

Collected course bibliography:

  • [slides] [handout] [lecture]



Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported License.