Difference between revisions of "Social production of knowledge by online communities"

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Supervisor: [[User:MarcoColombetti| Marco Colombetti]]
 
Supervisor: [[User:MarcoColombetti| Marco Colombetti]]
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https://www.politesi.polimi.it/handle/10589/56767
  
 
==== Abstract ====
 
==== Abstract ====

Latest revision as of 11:53, 19 November 2014

PhD Thesis of David Laniado

Supervisor: Marco Colombetti

https://www.politesi.polimi.it/handle/10589/56767

Abstract

In recent years a new paradigm has emerged on the Web, characterized by the massive participation of users in the production of content. The results present the typical advantages of a bottom up process: information tends to cover the most various topics, keeping up to date and reflecting the point of view of the users, giving prominence to the most popular ideas but representing also the long tail of diverse views. On the downside, social Web applications suffer for a lack of organization; the absence of a single coherent point of view, in conjunction with scarcely structured content, makes it harder to retrieve and organize information. The Semantic Web offers standards and tools for the representation of knowledge in structured format, but most online communities appear as still far and sometimes reluctant to the adoption of these solutions, which can hardly deal with the simple and quick interfaces that characterize Web 2.0 applications, and with the messy heterogeneous data created by many different-minded users.

This work presents an investigation on how the new bottom up paradigm based on the participation of large masses of users on the Web can deal with production and organization of knowledge on a large scale. Starting from the observation of emerging dynamics, mechanisms and conventions adopted by online communities to manage content, this thesis presents an insight into the main challenges raised by the huge amount of etherogeneous data created by users on the social Web, focusing on three of its pillars: microblogging, social tagging and wikis. A variety of approaches, ranging from information retrieval and social network analysis to Semantic Web technologies, are leveraged to shed light on interaction patterns which characterize content production in these systems, to assess their value as sources of structured knowledge, and to propose solutions which can improve current applications.