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Doing a Coolhunt/Social Network Analysis of Your Own
This is an individual project as a precursor to the team project, applying the Condor social network analysis and Web coolhunting tools on a topic of your choice. You have two options:
- Doing an in-depth analysis of your own mailbox, to uncover the key influencers in your own social network, similar to the examples introduced in class.
- Applying the coolhunting blueprint introduced in class, do a Web trend monitoring and analysis task on a topic of your own choice.
You can do this project either by yourself, or at most in teams of two. You need to have chosen the topic at the latest by Ses #6. It is due Ses #12. As part of the project, you will also get an individual task (the midterm exam on Ses #12), to be done individually, but in the classroom, without the instructor present.
Presenting a Research Paper in Class
In teams of three, you are asked to present one of these topics and its associated three to four papers in class (about a 30 minute presentation) putting it in perspective with latest trends and developments, and lead a 60 minute discussion with your classmates.
SES # | TOPICS | PAPERS |
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16 | Facebook (Group A) |
Aral, Sinan, and Dylan Walker. “Creating Social Contagion Through Viral Product Design: A Randomized Trial of Peer Influence in Networks.” Management Science 57, no. 9 (2011): 1623–39. Traud, Amanda L., Peter J. Mucha, et al. “Social Structure of Facebook Networks.” Hill, R. A., and R. I. M. Dunbar. “Social Network Size in Humans.” Human Nature 14, no. 1 (2003): 53–72. |
18 | Wikipedia (Group B) |
Kittur, Aniket, and Robert E. Kraut. “Harnessing the Wisdom of Crowds in Wikipedia: Quality Through Coordination.” CSCW ‘08 Proceedings of the 2008 ACM conference on Computer supported cooperative work, 2008. Liu, Jun, and Sudha Ram. “Who Does What: Collaboration Patterns in the Wikipedia and Their Impact on Data Quality.” ACM Transactions on Management Information Systems 2, no. 2 (2011): 175–80. Welser, Howard T., Dan Cosley, et al. “Finding Social Roles in Wikipedia.” Proceedings of the 2011 iConference, 2011. |
19 | Altruism & Behavioral Economics (Group C) |
Judge, Timothy A., and John D. Kammeyer-Mueller. “Happiness as a Societal Value Why Happiness Is Worthy of Study.” Academy of Management Perspectives 25, no. 1 (2008): 30–42. Frey, Bruno S. “Happy People Live Longer.” Science 331, no. 6017 (2011): 542–3. Ariely, Dan, Uri Gneezy, et al. “Large Stakes and Big Mistakes.” Review of Economic Studies 76, no. 2 (2009): 451–69. |
24 | Twitter and Prediction Markets (Group D) |
Bollen, Johan, Bruno Goncalves, et al. “Happiness is Assortative in Online Social Networks.” Artificial Life 17, no. 3 (2011): 237–51. Bollen, Johan, Huina Mao, et al. “Twitter Mood Predicts the Stock Market.” Journal of Computational Science 2, no. 1 (2011): 1–8. Wolfers, Justin, and Eric Zitzewitz. “Prediction Markets.” Journal of Economic Perspectives 18, no. 2 (2004): 107–26. Ott, Myle, Yejin Choi, et al. “Finding Deceptive Opinion Spam by Any Stretch of the Imagination.” HLT ‘11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, 2011. |
SES # | TOPICS | CONTENT AND READINGS | KEY DATES |
---|---|---|---|
1 | Collaboration science framework |
Gloor, Peter A. Swarm Creativity, Competitive Advantage Through Collaborative Innovation Networks. Oxford University Press, 2006. ISBN: 9780195304121. [Preview with Google Books] |
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2 | Condor 1 | Introduction to Condor. Web-coolhunting, and the “communication view” to measure the popularity of topics. Download and install Condor prior to class. Information on Condor can be found in the Software section of this course. | |
3 | Social network analysis |
Hands-on with Gephi. Wassermann, Stanley, and Katherine Faust. Social Network Analysis: Methods and Applications. Cambridge University Press, 1994. ISBN: 9780521387071. [Preview with Google Books] |
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4 | Condor 2 | Analyzing Twitter feeds and Facebook friends and walls. Visualizing and analyzing these results with Gephi. | |
5 | Measuring brands, concepts, people | What is the context and sentiment on the Web, Blogs, Facebook and Twitter of a brand or product? How can we measure the success of Web campaigns? How can we find the most influential people? | |
6 | Condor 3 | Analyzing your own mailbox, visualizing and analyzing the social network and the contents network (term view). | |
7 | Collective prediction | Predicting trends on the global level by mining the Web, Blogs, online forums, and Twitter. Examples include “Who will win the Oscars?”, political elections, and movie box office success. | |
8 | Group analysis | Analyzing the success of startup entrepreneurs (Israel, Boston biotech, XING cases). Creating Collaborative Care Networks (C3N). | |
9 | No class—Holiday | ||
10 | Midterm project 1 | Condor coolhunting team project | |
11 | Midterm project 2 | Condor coolhunting team project (cont.) | |
12 | Midterm project 3 | Midterm exam |
Individual coolhunting assignment due In-class midterm exam |
13 | Virtual status meeting | Jointly with Helsinki/Cologne/SCAD. Team formation on Flashmeeting. | |
14 | Sociometric badges | Analyzing individual creativity and knowledge flow optimization. | |
15 | Virtual status meeting | Virtual project update with Flashmeeting with Savannah, Cologne, Helsinki students and instructors. | |
16 |
Student presentation:Aral, Sinan, and Dylan Walker. “Creating Social Contagion Through Viral Product Design: A Randomized Trial of Peer Influence in Networks.” Management Science 57, no. 9 (2011): 1623–39. Traud, Amanda L., Peter J. Mucha, et al. “Social Structure of Facebook Networks.” Hill, R. A., and R. I. M. Dunbar. “Social Network Size in Humans.” Human Nature 14, no. 1 (2003): 53–72. |
Group A presentation due | |
17 | Virtual mirror | Presentation of team networking results—analyzing communication in class using dynamic social network analysis and Condor. | |
18 | Wikipedia |
Learning from Wikipedians for efficient open source project management in different cultures. Student presentation:Kittur, Aniket, and Robert E. Kraut. “Harnessing the Wisdom of Crowds in Wikipedia: Quality Through Coordination.” CSCW ‘08 Proceedings of the 2008 ACM conference on Computer supported cooperative work, 2008. Liu, Jun, and Sudha Ram. “Who Does What: Collaboration Patterns in the Wikipedia and Their Impact on Data Quality.” ACM Transactions on Management Information Systems 2, no. 2 (2011): 175–80. Welser, Howard T., Dan Cosley, et al. “Finding Social Roles in Wikipedia.” Proceedings of the 2011 iConference, 2011. |
Group B presentation due |
19 | Altruism and behavioral economics |
Coolfarming—Nurturing COINs in the virtual and real world. Self-organizing, intrinsically motivated project management. To become a better manager stop being a manager. Student presentation:Judge, Timothy A., and John D. Kammeyer-Mueller. “Happiness as a Societal Value Why Happiness Is Worthy of Study.” Academy of Management Perspectives 25, no. 1 (2008): 30–42. Frey, Bruno S. “Happy People Live Longer.” Science 331, no. 6017 (2011): 542–3. Ariely, Dan, Uri Gneezy, et al. “Large Stakes and Big Mistakes.” Review of Economic Studies 76, no. 2 (2009): 451–69. Hassanpour, Navid. “Media Disruption Exacerbates Revolutionary Unrest: Evidence from Mubarak’s Natural Experiment.” APSA 2011 Annual Meeting Paper (2011). |
Group C presentation due |
20 | Coolhunting results | Presentation of online social network analysis and prediction results. | |
21 | No class—Q&A final project work | ||
22 | No class—Holiday | ||
23 | Virtual status meeting | Virtual project update with Flashmeeting with Savannah, Cologne, Helsinki students and instructors. | |
24 | Twitter and prediction markets |
Student presentation:Bollen, Johan, Bruno Goncalves, et al. “Happiness is Assortative in Online Social Networks.” Artificial Life 17, no. 3 (2011): 237–51. Bollen, Johan, Huina Mao, et al. “Twitter Mood Predicts the Stock Market.” Journal of Computational Science 2, no. 1 (2011): 1–8. Wolfers, Justin, and Eric Zitzewitz. “Prediction Markets.” Journal of Economic Perspectives 18, no. 2 (2004): 107–26. Ott, Myle, Yejin Choi, et al. “Finding Deceptive Opinion Spam by Any Stretch of the Imagination.” HLT ‘11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, 2011. |
Group D presentation due |
25 | No class—Q&A final project work | ||
26 | Coolfarming results | Presentation of final results and insights of coolhunting and coolfarming projects. | Group project due |
This series of presentations provides information to further your understanding of the course content and software.
LEC # | TOPICS | LECTURE NOTES |
---|---|---|
1 | Collaborative Innovation Networks (COINs) | (PDF) |
2 | Introduction to swarm creativity and COINs | (PDF - 1.2MB) |
3 | Cool coolhunts | (PDF - 1.9MB) |
4 | Social network analysis: Basic concepts, methods, and theory | (PDF - 1.2MB) (Courtesy of Johannes Putzke. Used with permission.) |
5 | Create Gephi graphs from Condor data | (PDF) |
6 | Analyzing Collaborative Care Networks (C3N) | (PDF - 2.6MB) |
7 | Social me: What your social network tells you | (PDF - 2.3MB) |
8 | Getting started with Condor | (PDF - 2.9MB) |
9 | Coolhunting blueprint | (PDF - 1.4MB) |
10 | Coolhunting WWF | (PDF - 1.4MB) |
11 | What is coolhunting? | (PDF - 1.2MB) |
12 | Coolfarming: How to unlock the power of your COINs | (PDF - 1.4MB) |
In the second half of the seminar, small student teams with participants from MIT, Savannah College of Art and Design (SCAD), Aalto University Helsinki, and University of Cologne, Germany will work on their own trend analysis, prediction, and viral marketing projects using Web mining and dynamic SNA tools and methods, gaining invaluable insights about global virtual collaboration and about themselves as members of cross-disciplinary global virtual teams.
Descriptions of projects completed by students in the course are available below.
Social Innovation with “CreateHere”
While there are many pockets of social innovation around the world, the results of these efforts are mainly local. How might we connect these localized nodes of action and scale up social innovation in order to (1) to diffuse and improve upon process models for social innovation and (2) to recruit and train more people in becoming social innovators? Goals for this project include using dynamic social network analysis (SNA) s/w tools to capture and interpret the “buzz” around social innovation in (3) identifying and/or constructing methods of analyzing/replicating/scaling identified transformative social innovations and also potentially building policy platforms from the analysis of social innovation; and (4) visualizing these pockets and finding ways to broker new connections. This can take the form of intervening to ‘glue’ them together, rather than build some new structural element with the idea that once contexts are threaded together successfully new structures will emerge to support it.
In this project we will work with “CreateHere”, a group of Chattanooga residents and new recruits working for arts, economic, and cultural development, unified by the belief that place-making and connectivity are the source of innovation.
Coolfarming YouApp
Based on one of the COINs seminar projects of last year, the goal of the project is to further develop and grow the user community of YouApp. YouApp is a community-building platform integrated into Facebook. It addresses patients with inflammatory bowel disease (IBD; including Crohn’s disease and ulcerative colitis) and their primary caregivers by connecting them on Facebook. YouApp does this in two ways: It shows the user—patient or caregiver—how they fit in, by displaying their social network and how they are embedded in it. Second, it allows users to find and make new friends on Facebook who share similar interests and concerns. While a first prototype has been developed, much development work still remains to be done. The second, and even bigger challenge, is to recruit and nurture a user community of YouApp users, who will use it to find friends and hang out in this virtual community.
Creating GalaxyIndex
The goal of this project is to create an index about the big megatrends of humanity: nutrition, energy, communication, and health. Using the Condor coolhunting tools, this project strives to create four indices similar to Dow Jones, S&P, or NASDAQ, also including volatility information such as the VIX that track consumer sentiment and latest research developments in these four areas. Towards that goal, different information sources such as Wikipedia, Twitter, Blogs, and scientific paper collections should be continuously collected and tracked to define, develop, and maintain four indices.
Analyzing Social Movements in the 2011 Chilean Student Unrest
Using social media archives of the 2011 Chilean student unrest and dynamic social network analysis, we study how leaders and participants use social media such as Twitter, Facebook, Wikipedia, and Blogs to self-organize and communicate with each other. We trace the emergence of the movement, from an early call of students to more equitable access to the countries three-class basic education and expensive semi-private university system, to an unrest infecting the entire population, with blue-collar mining and factory workers now asking for fairer access to the country’s wealth derived from Chile’s vast natural resources. This project is in collaboration with Universita Cattolica di Santiago de Chile.
Predicting Travel Destinations from Mexico
In a joint project with online marketing agency Wannaflock and AeroMexico we identify key traveller forums similar to TripAdvisor for Mexican travelers as well as public sources such as Twitter and Facebook. Based on online discussions of travelers about popular destinations we try to predict future popularity of new travel destinations, to help identify AeroMexico potential new destinations, and at what frequency and with which size plane to fly to existing destinations.
This course requires extensive use of Condor, a dynamic social network analysis software. To learn more about the Condor software, please watch the following video:
Welcome to Condor (This video was created by Galaxy Advisors and is not covered under our Creative Commons license.)
Step by step instructions on accessing and downloading the Condor software are available:
Course Meeting Times
Lectures: 2 sessions / week, 2 hours / session
Course Perspective and Description
The emergence of online social networks opens up unprecedented opportunities to read the collective mind, discovering emergent trends while they are still being hatched by small groups of creative individuals. The Web has become a mirror of the real world, allowing researchers in predictive analytics to study and better understand why some new ideas change our lives, while others never make it from the drawing board of the innovator.
Diversity begets creativity—in this seminar we tap the amazing power of swarm creativity on the Web by studying and working together as Collaborative Innovation Networks (COINs). As interdisciplinary teams of MIT management, Savannah College of Art and Design, University of Cologne informatics, and Aalto University software engineering students we will explore how to discover latest trends on the Web, and how to make them succeed in online social networks.
We study a wide range of methods for predictive analytics (coolhunting) and online social marketing (coolfarming), mostly based on social network analysis and the emerging science of collaboration. Our methods are based on analysis of large corpora of digital traces of human activity, in particular the Web, Blogs, online forums, social networking sites, e-mail archives, phone logs, and face-to-face interaction through using sociometric badges. Students will also learn to use our own unique MIT-developed Condor tool for Web mining, social network analysis, and trend prediction.
Students will be asked to do preparatory readings. During class, small teams will be asked to present an overview of research topics based on the papers listed below. In the second half of the seminar, small student teams with participants from MIT, SCAD, Aalto University (Helsinki), and University of Cologne (Germany) will work on their own trend analysis, prediction, and viral marketing projects using Web mining and dynamic SNA tools and methods, gaining invaluable insights about global virtual collaboration and about themselves as members of cross-disciplinary global virtual teams.
Course Norms and Expectations
Because this course relies heavily on class participation for its success, class norms and expectations regarding class behavior are very important:
- Attendance at every class is required. Please schedule outside activities at times other than when 15.599 meets. Please arrive on time and stay from the beginning of class to the end. You are allowed up to two excused absences before missing class seriously affects your grade. For classes you must miss, it is your responsibility to find out from your classmates what materials were covered, what items were distributed in class, and what key points were collectively advanced.
- Please come to class prepared to discuss the readings. For each theory class a small team of students is asked to briefly present major findings and prepare a set of questions to guide the others through the discussion.
- For the teamwork and virtual collaboration sessions, being globally connected is essential, so bring your laptop to be able to connect with colleagues at other locations in virtual collaboration sessions (Savannah, Helsinki, Cologne) for the second half of the course (virtual collaboration sessions unavailable to OCW users).
Grading
ACTIVITIES | PERCENTAGES |
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Class participation | 20% |
Midterm project | 20% |
Case presentations | 20% |
Final team project | 40% |