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Social Data and Behavior Change
Social Data and Mobility
Social Data Predictions for 2020
is a wiki. What does this mean?
If you see anything that can be improved, just do it. While everybody can view, only members can edit. All students in the class have been added as members based on their Stanford email addresses. If there is any access problem, please click on the top of this page, and generate a request to be added as editor of the wiki.
Previous year's course wikis are available:
| Management Science and Engineering, Stanford University
Social Data Revolution
| MS&E 237 (Spring 2011)
Time: Tue, Thu 4:15PM - 5:30 PM | Location: 200-303 (History Corner)
SYLLABUS (aka home page
Social Data Revolution
? The amount of data generated by people doubles roughly every 1.5 years. The plummeting costs of creating, gathering, storing, distributing, and indexing data have a tremendous impact on the expectations of individuals as they create and share information about themselves and their relationships with others, both in a C2W context (consumer-to-world, e.g., Twitter) and a C2C context (e.g., Facebook). This has ignited the Social Data Revolution.
This course will discuss the new data sources, and how can they be used to create value for individuals, business, and ultimately society.
Instructor: Andreas Weigend (
Office hour (
): Tue 2:00 PM - 3:00 PM in Andreas's office (Huang 354, 475 Via Ortega, located on the NE corner of Panama Street and Via Ortega, behind the Y2E2 Building), and by appointment. Please drop me an email, and if you think you should have received a response but didn't, then text or call (650) 906-5906.
Course assistant: Jason Wei (firstname.lastname@example.org)
Office hour: Mon 2:00 PM - 3:00 PM at Coupa Cafe (near Meyer Library, not near Y2E2)
The schedule is also at
. Assignments are at noon on the dates given in this class-by-class schedule.
for short updates.
(extended to Friday June 3, 2011 at noon) [aweigend]
Participate in the
Social Data Lab
. It is especially important to links to the wikipedia age from related articles to get to get it un-orphaned!
Grading policy (total 100 points)
you signed up for (1 x 10 points)
12.5: Other wikis you contributed to, and class participation
(7 x 2.5 points each)
60: HWs (4 x 15 points each)
Given the selection process for this students in this class, this class will not be graded on a curve.
Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites
is important for the first two homework assignments.
The class representatives were elected in the first week of the quarter to serve as liaison between instructors and students.
MS&E: Aldo Briano <email@example.com>
GSB: Sameh Mohamed El Amawy <Elamawy_Sameh@GSB.Stanford.Edu>
Other graduates: Andreas Nomikos <firstname.lastname@example.org>
Undergraduates: Lucas Duplan <email@example.com>
They form the class advisory board that meets four times during the quarter:
April 19 (8pm Pasta?)
May 3 (8pm CoHo)
May 27 (8pm San Francisco)
Please talk to them about any feedback and suggestions you might have!
Directions to the classroom
For guests, the following information might be useful: If you come by car, a convenient parking area is the street parking (you need to pay until 4pm) in front of the Cantor Center for the Visual Arts (328 Lomita Drive, Stanford CA 94305). After parking, walk for a few minutes (continuing in the same direction) towards the central part of campus. The first real street you will reach (not counting the street at the museum) is called Serra Mall
If you want to go to the classroom directly, turn left on Serra Mall. The class is in the leftmost corner of the Quad, Building 200 ("History Corner")
And if you want to grab a bite or a cup of coffee, turn right on Serra Mall and cross the street to get to Bytes Cafe, located at the ground floor of David Packard Electrical
Engineering, across the street from Gates Computer Science.
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