Web Science/Part2: Emerging Web Properties/Collective Intelligence

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Part1: Foundations of the web

Part2: Emerging Web properties

Part3: Behavioral Models

Part4: Web & society

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About the Web Science MOOC

Course elements  

• PART1: Week1: Ethernet · Internet Protocol  · Week2: Transmission Control Protocol · Domain Name System · Week3: Internet vs world wide web · HTTP · Week4: Web Content  · Dynamic Web Content
• PART2: Week5: How big is the Web?  · Descriptive Web Models  · Week6: Advanced Statistic Models  · Modelling Similarity  · Week7: Generative Modelling of the Web · Graph theoretic Web Modelling
• PART3: Week8 : Investigating Meme Spreading  · Herding Behaviour  · Week9: Online Advertising  · User Modelling
• PART4: Week10 : Copyright  · Net neutrality  · Week11: Internet governance  · Privacy

9th week due Jan 10th The Web as a Social Machine: Collective intelligence and Human Computing Definition of collective intelligence Examples of collective intelligence pagerank Mechanisms behind collective intelligence "natural" distributions * e.g. Gaussian error for estimating size of an object * e.g. natural bias toward positive for evaluation of products (where do we re-find a paper for this?) "averaging" in some sense * high enough systematic error leads to optimal estimation independent assessment! Google Flu Trends and its Limits http://www.sueddeutsche.de/wissen/big-data-google-versagt-bei-grippe-vorhersagen-1.1912226 http://www.nature.com/nature/journal/v457/n7232/abs/nature07634.html http://www.sciencemag.org/content/343/6176/1203 Models of attention attention models (Lehrman) Conclusion: Collective intelligence may be jeopardized by the social setup of the system