Computational Social Science

I have recently been intrigued about the evolving science of social network analysis (SNA) and the potential novel yet practical applications of it in growing businesses. So the timing of the 3rd Annual Stanford Conference on Computational Social Science, hosted by IRiSS could not have been better.

Fun day with very cool thoughts, from the keynote of the superstar in the field, Duncan “small worlds” Watts to very practical insights from Facebook and Google scientists to usage of SNA on unusual datasets such as the englightement-era snail mail metadata (who was the bridging node between Voltaire and Ben Franklin?) to the intricacies of linguistic change (“aroma” getting replaced by “smell”) in beer enthusiast forums.

Some assorted notes and further reading links are below.

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Week 40: The End of Class Notes

Stanford GSB Sloan Study Notes, Week 10 (40), Spring quarter

Chuck Holloway

Our last two days of five classes were almost all about presentations with a few wise final words from each professor. Pictured above is the last of my last moments, with Professor Charles Holloway, co-founder of Stanford’s Center for Entrepreneurial Studies, and a driving force behind many startup-focused academic initiatives in this school over the decades. My last class co-incidentally was the very last Formation of New Ventures Chuck taught for 16 years together with John Morgridge of Cisco fame.

I am sad this is over, not counting one remaining exam. And glad I made it here in time to be part of so many defining classes like this over the past year. I guess it is up to us now to walk out of this campus in the footsteps of many whom these teachers have personally sent off to change the world over the years.

John’s closing words included “don’t try to do it all by 35”. Relieved to know, having crossed that milestone at Stanford.

Covered in this issue:

  • very brief summary remarks from professors concluding their quarter
  • Last Lecture by JetBlue Chairman Joel Peterson

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Week 33: Network Centrality, Bass Diffusion, SaaS Sales & Data Science

Stanford GSB Sloan Study Notes, Week 3 (33), Spring quarter

Head down in two inches of readings for this week and a fresh flow of first written project deadlines, like a two-degrees-deep analysis of your friends and advisors social graph or a set of regressions to be run on profitability data of a bank who has no clue if there is any connection between the demographics and profitability of their customers.

For a little different entertainment in the Sales Orgs class we are running a simulation game where you need to manage yourself through the pipeline as a sales rep of a medical devices company. Four virtual “years” in four weeks. After a miserable first year (I hit merely about a quarter of my quota – should have read the manual before I tried to just figure the game mechanics out for 2 “quarters”) I look forward to the Tuesday class from a much more comfortable position after “year” 2. I guess the hours spent as a teen with Civilization and the likes can sometimes pay off?

GSB hosted a fun networking event this week called “Fewer than 300” – bringing people in from over 30 companies who are about to grow out of their startup phase (but are yet to break 300 employees), but have raised money and shown traction and still are just burning of enthusiasm about what they are doing. Think of the likes of Uber or Nest or Visual.ly. Good people and good conversations.

Covered in this issue:

  • Analysing network centrality measures and deriving composite relationships from simple a matrix
  • Using Bass diffusion models for new product adoption predictions
  • Handling variability in processes (from job shops to continuous flow)
  • Economics of selling SaaS subscriptions and merging sales teams after M&A
  • More team-first entrepreneurial models
  • History of Sloan Program at Stanford
  • Data Science learnings from LinkedIn and other Greylock companies
  • Guests: Vinod Khosla, Mark Leslie & part of Veritas exec team, Corey Leibow, Eric Botto, George Parker, DJ Patil

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