When Computation met Society

Election time, and the predicting is easy…

As I am sure you have heard, the Iowa caucus results are in. Several journalists are reporting on the elections along with claims of “predictions” that social media are supposedly making. And the day after the Iowa caucus, they are wondering whether Twitter predicted correctly or not. And they look at the “professionals” for advise such as Globalpoint, Sociagility, Socialbackers and other impressive sounding companies.

Shepard Fairey meets Angry Birds: Poster of our 2011 ICWSM submission "Limits of Electoral Predictions using Twitter"

Well, Twitter did not get it right. That is not surprising to my co-authors and I.  Yet, they try to find a silver lining, by claiming smaller predictions such as “anticipating Santorum’s excellent performance than the national polls accomplished.” Of course, the fact that Twitter missed the mismatches with the other 5 candidates is ignored. Why can’t they see that?

A few years ago I had created a questionnaire to help my students sharpen their critical thinking skills. One question that the vast majority got right was the following: “Is Microsoft the most creative tech company?” If one were to do a Web search on this question, the first hit (the “I feel lucky” button) would be Microsoft’s own Web page, because it had as title “Microsoft is the most creative tech company.” My students realized that Microsoft may not be providing an unbiased answer to this question, and ignored it.

It is exactly this critical thinking principle that journalists obsessed with election predictions are getting wrong: The companies I mentioned above ( Globalpoint, Sociagility, Socialbackers ) are all in the business of making money by promising magical abilities in their own predictions and metrics. One should not take their claims on face value because they have financial conflict of interest in giving misleading answers (e.g. “Comparing our study data with polling data from respected independent US political polling firm Public Policy Polling, we discovered a strong, positive correlation between social media performance and voting intention in the Iowa caucus.” Note that even after the elections they talk about intentions, not results.)

That’s not the only example violating this basic critical thinking principle I saw today. Earlier, I had received a tweet that “Americans more susceptible to online scams than believed, study finds“. The article reports that older, rich, highly educated men from the Midwest, politically affiliated with the Green Party are far less susceptible to scam than young, poor, high school dropout women from the Southwest that are supporting Independents. If you read the “study” findings, you will be even more confused about the quality of this study. A closer look reveals that the “study” was done by PC Tools, a company selling “online security and system utility software.” Apparently, neither the vagueness of the “survey” nor the financial conflict of interest of the surveying company raised any flags for the reporter.

In the Web era, information is finding us, not the other way around. Being able to think critically will be crucial.

The deadline for the Special Issue on Social Media for the German Journal of Artificial Intelligence (Kuenstliche Intelligenz) is coming up. We invite you to submit your article by the FEBRUARY 6, 2012 deadline. It will be published later this year by Springer.

If you intent to submit but the deadline is too close to catch, send me an email!

The Theme of the Special Issue

Social Media has led to radical paradigm shifts in the ways we communicate, collaborate, consume,  and create information. Technology allows virtually anyone to disseminate information to a global  audience almost instantaneously. Information published by peers in the form of Tweets, blog posts,  or Web documents through online social networking services has proliferated on an unprecedented  scale, contributing to an exponentially growing data deluge. A new level of connectedness among  peers adds new ways for the consumption of (traditional) media. We are witnessing new forms of  collaboration, including the phenomenon of an emergent ‘collective intelligence’. This intelligence of  crowds can be harnessed in myriad ways, ranging from outsourcing simple, repetitive tasks on  Amazon Mechanical Turk, to solving complex challenges such as proving a mathematical theorem  creatively and collaboratively.

This call for papers welcomes contributions showing:

1. How to make sense of Social Media data, i.e. how to condense, distill, or integrate highly  decentralized and dispersed data resulting from human communication, including sensor-­‐collected  data to a meaningful entity or information service, or
2. How Social Media contributes to innovation, collaboration, and collective intelligence.

We invite papers covering all aspects of Social Media analysis including Social Media in Business  (especially for Marketing, Innovation, and Collaboration), Entertainment (especially Social News,  Social Music Services, Social TV, and Social Network Games), as well as Art (e.g. City Installations).  Applications of Social Media in art may be understood as a playing field for translating highly  decentralized ‘social data’ into centralized forms of artful expression, thus furthering our intuitive  understanding of these complex emergent phenomena.

List of topics

The list of topics mentioned below is neither exhaustive nor exclusive. Insightful artifacts and  methods as well as analytical, conceptual, empirical, and theoretical approaches (using any kind of  research method, including experiments, primary data from social media logs, case studies,  simulations, surveys, and so on) are within the scope. Practical project descriptions and innovative  software are also of high interest to the readers of KI.

•  Information/Web mining (e.g. opinion mining)
•  Prognosis (e.g. trend and hot topic identification)
•  Collective Intelligence
•  Crowd sourcing
•  Swarm Creativity, Collaborative Innovation Networks
•  (Dynamic) Social Media Monitoring
•  Sentiment, Natural Language Processing
•  Social Media within and for Smart Cities, Smart Traffic, Smart Energy
•  Social Networks for the collaboration of large communities
•  User behavior, social interaction
•  Social Network Analysis (SNA), semantic network analysis
•  Social search engines and aggregators
•  Social network games
•  Personalization and adaptation to user preference
•  Trust, reputation, social control, privacy
•  Information reliability, Web spam, content authenticity (e.g., detecting “astroturfing”)

Deadlines

• Submissions open until February 6, 2012 (extended)
• Camera-­‐ready copies of revised papers by April 30, 2012
• Pre-­‐Publication of accepted papers via Springer Online First in June 2012
• Printed version of this Special Issue: Fall 2012

In addition to complete research papers, this Special Issue will accept project and dissertation reports  as well as discussion and conference reports in order to provide a comprehensive overview of the  current activities in this area.

 Guest Editors    

• Detlef Schoder, Prof. Dr., schoder@wim.uni-­koeln.de,
  University of Cologne (Koeln),  Department of Information Systems and Information Management, Cologne, Germany
• Peter A. Gloor, PhD, pgloor@mit.edu,
  MIT Sloan School of Management, Center for  Collective Intelligence, Cambridge, MA, USA
• Panagiotis Takis Metaxas, PhD, Prof., pmetaxas@seas.harvard.edu,
  Wellesley College,  Department of Computer Science, Wellesley, MA, and Harvard University, Center for  Research on Computation and Society, Cambridge, MA, USA

For inquiries and submissions please contact:

Prof. Dr. Detlef Schoder
University of Cologne (Koeln),
Department of Information Systems and  Information Management,
Pohligstrasse 1, D-­‐50969
Cologne/Germany,
Phone: +49 / (0)221 470-­5325,
Fax: +49 / (0)221 470-­5393,
URL: http://www.wim.uni-­koeln.de/,
Email: schoder@wim.uni-­koeln.de