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in Proceedings of The International Symposium on Open Collaboration (OpenSym '14) Publié en 2018-08 Nom de la conférence The International Symposium on Open Collaboration (OpenSym '14)
BORRA Erik
CIUCCARELLI Paolo
WELTEVREDE Esther
KALTENBRUNNER Andreas
LANIADO David
MAGNI Giovanni
MAURI Michele
ROGERS Richard
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Collaborative content creation inevitably reaches situations where different points of view lead to conflict. In Wikipedia, one of the most prominent examples of collaboration online, conflict is mediated by both policy and software, and conflicts often reflect larger societal debates. Contropedia is a platform for the analysis and visualization of such controversies in Wikipedia. Controversy metrics are extracted from activity streams generated by edits to, and discussions about, individual articles and groups of related articles. An article’s revision history and its corresponding discussion pages constitute two parallel streams of user interactions that, taken together, fully describe the process of the collaborative creation of an article. Our proposed platform, Contropedia, builds on state of the art techniques and extends current metrics for the analysis of both edit and discussion activity and visualizes these both as a layer on top of Wikipedia articles as well as a dashboard view presenting additional analytics. Furthermore, the combination of these two approaches allows for a deeper understanding of the substance, composition, actor alignment, trajectory and liveliness of controversies on Wikipedia. Our research aims to provide a better understanding of sociotechnical phenomena that take place on the web and to equip citizens with tools to fully deploy the complexity of controversies. Contropedia is useful for the general public as well as user groups with specific interests such as scientists, students, data journalists, decision makers and media communicators.

in The Routledge Handbook to Developments in Digital Journalism Studies Sous la direction de ELDRIDGE II Scott Publié en 2018-08
BOUNEGRU Liliana
GRAY Jonathan
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Networks are classic but under-acknowledged figures of journalistic storytelling. Who is connected to whom and by which means? Which organizations receive support from which others? What resources or information circulate through which channels and which intermediaries enable and regulate their flows? These are all customary stories and lines of inquiry in journalism and they all have to do with networks. Additionally, the recent spread of digital media has increasingly confronted journalists with information coming not only in the traditional form of statistic tables, but also of relational databases. Yet, journalists have so far made little use of the analytical resources offered by networks. To address this problem in this chapter we examine how “visual network exploration” may be brought to bear in the context of data journalism in order to explore, narrate and make sense of large and complex relational datasets. We borrow the more familiar vocabulary of geographical maps to show how key graphical variables such as position, size and hue can be used to interpret and characterise graph structures and properties. We illustrate this technique by taking as a starting point a recent example from journalism, namely a catalogue of French information sources compiled by Le Monde’s The Decodex. We establish that good visual exploration of networks is an iterative process where practices to demarcate categories and territories are entangled and mutually constitutive. To enrich investigation we suggest ways in which the insights of the visual exploration of networks can be supplemented with simple calculations and statistics of distributions of nodes and links across the network. We conclude with reflection on the knowledge-making capacities of this technique and how these compare to the insights and instruments that journalists have used in the Decodex project – suggesting that visual network exploration is a fertile area for further exploration and collaborations between data journalists and digital researchers.

In this article, we present a few lessons we learnt in the establishment of the Sciences Po médialab. As an interdisciplinary laboratory associating social scientists, code developers and information designers, the médialab is not one of a kind. In the last years, several of such initiatives have been established around the world to harness the potential of digital technologies for the study of collective life. If we narrate this particular story, it is because, having lived it from the inside, we can provide an intimate account of the surprises and displacements of digital research. Founding the médialab in 2009, we knew that we were leaving the reassuring traditions of social sciences to venture in the unexplored territory of digital inscriptions. What we couldn't foresee was how much such encounter would change our research. Buying into gospel of Big Data, we imagined that the main novelty of digital research came from handling larger amounts of data. We soon realized that the interest of digital inscriptions comes instead from their proliferating diversity. Such diversity encouraged us to reshape our professional alliances, research practices and theoretical perspectives. It also led us to overcome several of the oppositions that used to characterize social sciences (qualitative/quantitative, situation/aggregation, micro/macro, local/global) and to move in the direction of a more continuous sociology.

Publié en 2017-04 Nom de la conférence Journalism & the Search for Truth in an Age of Social Media
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in Datafied Society: Social Research in the Age of Big Data. Publié en 2017-02-25
BOUNEGRU Liliana
GRAY Jonathan
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No doubt, networks have become indispensable mathematical tools in many aspects of life in the twenty first century. They allow us to calculate all kinds of relational metrics and to quantify the properties of their nodes, clusters and global structures. These modes of calculation are becoming increasingly prevalent in an age of digital data. But networks are more than formal analytical tools. They are also powerful metaphors of our collective life, with all of its complexity and its many dependencies. This is why, among the various strategies of data visualization, networks seem to have assumed a paradigmatic position, spreading to the most different disciplines and colonizing sometimes as mere decoration a growing number of digital and non-digital objects. Contemplating the visual representation of a network, we don’t (always) need to compute its mathematical properties to appreciate its heuristic value – as anyone who has ever used a transportation plan knows well. Networks are extraordinary calculating devices, but they are also maps, instruments of navigation and representation. Not only do they guide our steps through the territories that they represent, but they also invite our imagination to see and explore the world in different ways. [First paragraph]

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Networks have become the de facto diagram of the Big Data age (try searching Google Images for [big data AND visualisation] and see). The concept of networks has become central to many fields of human inquiry and is said to revolutionise everything from medicine to markets to military intelligence. While the mathematical and analytical capabilities of networks have been extensively studied over the years, in this article we argue that the storytelling affordances of networks have been comparatively neglected. In order to address this we use multimodal analysis to examine the stories that networks evoke in a series of journalism articles. We develop a protocol by means of which narrative meanings can be construed from network imagery and the context in which it is embedded, and discuss five different kinds of narrative readings of networks, illustrated with analyses of examples from journalism. Finally, to support further research in this area, we discuss methodological issues that we encountered and suggest directions for future study to advance and broaden research around this defining aspect of visual culture after the digital turn.

Publié en 2016-05 Nom de la conférence International AAAI Conference on Web and Social Media
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The web is a field of investigation for social sciences, and platform-based studies have long proven their relevance. However the generic web is rarely studied in itself though it contains crucial aspects of the embodiment of social actors: personal blogs, institutional websites, hobby-specific media… We realized that some sociologists see existing web crawlers as “black boxes” unsuitable for research though they are willing to study the broad web. In this paper we present Hyphe, a crawler developed with and for social scientists, with an innovative “curation-oriented” approach. We expose the problems of using web-mining techniques in social science research and how to overcome those by specific features such as step-by-step corpus building and a memory structure allowing researchers to redefine dynamically the granularity of their “web entities”.

Cet article reprend une recherche de Luc Boltanski sur les enseignants de l’IEP de Paris. Dans cette recherche, Boltanski s’appuie sur une représentation tabulaire des champs sociaux pour montrer que la classe dominante se caractérise avant tout par sa multipositionnalité, c’est-à-dire par la tendance de ses membres à occuper plusieurs positions dans plusieurs champs. En remplaçant le tableau de Boltanski par un graphe d’individus et d’institutions, nous discuterons les caractéristiques et les avantages d’une sociologie de réseaux hétérogènes.

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This paper discusses the differences and affinities among three types of networks (namely Actor-?Network, Network Analysis and Digital Networks) that are playing an increasingly important role in digital STS. In the last few decades, the idea of ‘network’ has slowly but steadily colonized broad strands of STS research. This colonization started with the advent of actor-?network theory, which provided a convenient set of notions to describe the construction of socio-?technical phenomena. Then came network analysis, and scholars who imported in the STS the techniques of investigation and visualization developed in the tradition of social network analysis and scientometrics. Finally, with the increasing ‘computerization’ of STS, scholars turned their attention to digital networks a way of tracing collective life. Many researchers have more or less explicitly tried to link these three movements in one coherent set of digital methods for STS, betting on the idea that actor-?network theory can be operationalized through network analysis thanks to the data provided by digital networks. Yet, to be honest, little proves the continuity among these three objects besides the homonymy of the word ‘network’. Are we sure that we are talking about the same networks? "Odi

The aim of the project MEDEA is to use digital mapping tools to try and trace the provenance and pivot points in these debates within different institutional settings. We look principally at the construction of scientific expertise in the Intergovernmental Panel on Climate Change (IPCC) and the evolution of adaptation as an issue within the international negotiations of the United Nations Framework Convention on Climate Change (UNFCCC). We also have a separate case study that follows regional deliberations on climate impacts and water management in the southwest of France. This website presents the results from the first two investigations of this ANR funded project, which was was made possible by a joint collaboration between social and data scientists (Sciences Po, médialab), climate scientists (Laboratoire des Sciences du Climat et l'Environnement) and designers (Ecole Nationale Supérieure des Arts Décoratifs). Experimental in its combination of disciplines and digital data methods, our mapping activities attempt to make legible to a non-expert public the institutional and topical transformations within the leading scientific and political arenas of the climate debate.

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