Andreas Weigend, Social Data Revolution | MS&E 237, Stanford University, Spring 2011 | Syllabus

Table of Contents

This is the place where we post ideas that can be used for extra credit for up to 20 points.

Due: Ideally by Tue May 24 (for feedback) and required by Thu May 26 2011 to get extra credit:
Deliverable: One crystal clear paragraph by each group of what it is you are doing, with all your names are incl contact info, and eventually links to where things can be found.


  • (2) 20 predictions for 2020 Predictions (Pao Jirakulpattana, Rhampapacht Vorapatchaiyanont (Joy) [varistha@stanford.edu], Addy Satija addy@stanford.edu)
    • On September 24, 2010 in Amsterdam, at the final day of PICNIC, a group of some 40 participants met to create scenarios and predictions for 2020. This session was led by Andreas Weigend after his keynote “Instrumenting the World: Data is King”. Our job is to make sure the blog post finally goes out.
    • Divide the prediction into different categories.
    • Wherever applicable, add in what we learn from class (such as the relationship between social data and organized crime)

  • (3) Social Data Intelligence Test (Aldo Briano abriano@stanford.edu, Tim Holley tholley@stanford.edu)
    • For an overview and to take the test go to: bit.ly/SDITest
    • Blog Post weigend.com/blog
    • Economist article submitted by Weigend on Tuesday June 7 2011

  • (4) YouTube.com/SocialDataRevolution (Misrab Faizullah-Khan, misrab@stanford.edu; Bhaskar Garg, bgarg@stanford.edu)
    1. Optimal number of videos to be put up on SDR/youtube website
      - Identify WHICH videos to actually put up as well
      - Identify WHY I chose them
      - Metrics will include: number of views, re-embedding (at the very least)

    2. How to make use of transcripts available
      - Specifically to promote the website
      - Some ideas: correlating key words with number of views...

    3. Identifying "types of users"
      - Leverage TubeMogul.com
      - Possibly determine player types that can gather more information from users for such analysis

  • (5) The Impact of Social Data on Mobility (Ruchi Varshney rvarshne, Eva Petrova-Ibarria evapi, Sebastiaan Boer sboer)
    • Mobility is one of the most promising areas in which social data can make an impact. Our research will look at how social data can create behavioral change and solve mobility issues. We will also look at how to incentivize people to share social data when they are travelling.
    • There are four types of mobility-related behavioral changes we can induce, namely the time of travel, the choice of transportation method, the destination and the decision whether to travel in the first place.
    • We will give a PHAME analysis of this issue, our hypothesis on how social data can impact mobility, what experiments and metrics can be used to measure the impact of social data. We will also give examples of mobility issues, what type of behavioral change would solve the issue, and show what data should be social to create this change of behavior.
    • We will also look at current technologies and companies that have the technology to collect social data and influence peoples' behavior.

  • (6) Summarizing the Social Data Lab meetings (Benjamin Ying bying@stanford.edu)

  • (7)Blog post on Zazzle and Justnear.me (Becky Nixon bnixon@stanford.edu, Emma Medjuck, emedjuck@stanford.edu, Fontaine Foxworth)

  • (8) Identifying popular campus dining halls among Stanford vegetarians via QR-code check-ins (Chris Sholley, csholley@stanford.edu)
    • I will post a map of vegetarian check-ins in campus dining halls at http://bit.ly/vegmap. I will debrief Stanford Dining about the benefits/challenges of using QR-codes to learn about student preferences. I will write a blog post about my experience on Justnear.me.



  • (9) Increasing the layman's understanding of the degree of influence of recommendation algorithms and prioritization functions have on our digital experience [aegupta@stanford.edu, leo.grimaldi@stanford.edu
    • An accessible blog post to trigger people to think about the "back-end" of our digital experiences (e.g., facebook, google, etc.); And how decisions made my these sites are affecting our front-end experiences.
    • A facebook survey(or http://dl.dropbox.com/u/9927844/Jing/2011-06-04_0942.png) to prompt people to consider how their facebook feed is prioritized
        • Surprisingly, the most popular response was to request for facebook to not prioritize their feed at all - which indicates that many people do not understand the degree to which Facebook is currently prioritizing their feed and the need for some filtering system to go through the plethora of news data.

  • (10) Blogpost: How does the deluge of data around us affect the way we behave? [davidkim@stanford.edu]
    • I will explore the following 3 ways in which we are being actively or inactively affected.
      1. Data as agnostic: This refers to data that is presented just as more information for the user to make a decision so behavior change is minimal.
      2. Social Engineering: This refers to systems deliberately created to actively change our behavior.
      3. Social Architecture: This refers to a less deliberate form of social engineering where a more neutral ecosystem for interaction is created

  • (11) Virtuous Reality or Real Virtuosity? [Sameh Elamawy, Jason Lee, evlarrub, mmarcott]