Manifesto of computational social science

The increasing integration of technology into our lives has created unprecedented volumes of data on society's everyday behaviour. Such data opens up exciting new opportunities to work towards a quantitative understanding of our complex social systems, within the realms of a new discipline known as Computational Social Science. Against a background of financial crises, riots and international epidemics, the urgent need for a greater comprehension of the complexity of our interconnected global society and an ability to apply such insights in policy decisions is clear. This manifesto outlines the objectives of this new scientific direction, considering the challenges involved in it, and the extensive impact on science, technology and society that the success of this endeavour is likely to bring about.The publication of this work was partially supported by the European Union’s Seventh Framework Programme (FP7/2007–2013) under grant agreement No. 284709, a Coordination and Support Action in the Information and Communication Technologies activity area (‘FuturICT’ FET Flagship Pilot Project). We are grateful to the anonymous reviewers for the insightful comments.Publicad

Amazon Mechanical Turk: A Research Tool for Organizations and Information Systems Scholars

Abstract. Amazon Mechanical Turk (AMT), a system for crowdsourcing work, has been used in many academic fields to support research and could be similarly useful for information systems research. This paper briefly describes the functioning of the AMT system and presents a simple typology of research data collected using AMT. For each kind of data, it discusses potential threats to reliability and validity and possible ways to address those threats. The paper concludes with a brief discussion of possible applications of AMT to research on organizations and information systems

Public Policy Formulation through Non Moderated Crowdsourcing in Social Media

Part 5: Techniques and AnalysisInternational audienceThe emergence of web 2.0 social media enables the gradual emergence of a second generation of e-participation characterized by more citizens’ control, in which government agencies post content (e.g. short or longer text, images, video) to various social media and then analyze citizens’ interactions with it (e.g. views, likes/dislikes, comments, etc.). In this paper we propose an even more citizens controlled third generation of e-participation exploiting web 2.0 social media as well, but in a different manner. It is based on the search by government agencies for content on a public policy under formulation, which has been created in a large set of web 2.0 sources (e.g. blogs and microblogs, news sharing sites, online forums) by citizens freely, without any initiation, stimulation or moderation through government postings. This content undergoes advanced processing in order to extract from it arguments, opinions, issues and proposals on the particular policy, identify their sentiments (positive or negative), and finally summarize and visualize them. This approach allows the exploitation of the vast amount of user-generated content created in numerous web 2.0 social media for supporting governments to understand better the needs, wishes and beliefs of citizens, and create better and more socially rooted policies