Output and publications

The project officially lasted from 2016 to the end of 2019.

We list here the main output, publications and software platforms.

International journal articles

  1. “Tubes & Bubbles – Topological confinement of YouTube recommendations”, Camille Roth, Antoine Mazières, Telmo Menezes, to appear in PLOS ONE, 2020.
  2. Poulain R., Tarissan F., “Investigating the Lack of Diversity in User Behavior: the Case of Musical Content on Online Platforms” Information Processing & Management, 7(2), 2020.
  3. “Interactional and Informational Attention on Twitter”, Agathe Baltzer, Márton Karsai, Camille Roth, Information, 10(8):250, 2019.
  4. Charbey R., Prieur C., “Stars, holes, or paths across your Facebook friends: A graphlet-based characterization of many networks” Network Science (2019), pp. 1-22.
  5. Arnoux T., Tabourier L., Latapy M., “Predicting interactions between individuals with structural and dynamical information” Journal of Interdisciplinary Methodologies and Issues in Sciences, 2019
  6. Gaumont, N., Panahi, M., Chavalarias, D., 2018. « Reconstruction of the socio-semantic dynamics of political activist Twitter networks—Method and application to the 2017 French presidential election” PLOS ONE 13, e0201879.
  7. “The semantic drift of quotations in blogspace: a case study in short-term cultural evolution”Sébastien Lerique, Camille Roth, Cognitive Science, 42(1):188-219 (2018)
  8. “Natural Scales in Geographical Patterns”, Telmo Menezes, Camille Roth. Scientific Reports (Nature), 7:45823. (2017)

International book chapters or conference proceedings

  1. Cardon (Dominique),  “How to rank the Web. Competition among metrics of digital information”, in Douay (Nicolas), Wan (Annie), dir., Big data and Civic engagement, Roma, Planum Publishers, July 2017, pp. 55-63
  2. Poulain R., Tarissan F., “Quantifying the diversity in users activity : an example study on online music platforms.” Proc. of SNAMS Conference, 2018.
  3. Ramaciotti Morales P., Tabourier L., Ung S., Prieur C., “Role of the Website Structure in the Diversity of Browsing Behaviors” Proceedings of the 30th ACM Conference on Hypertext and Social Media, pp. 133-142. ACM, 2019.
  4. “Automatic Discovery of Families of Network Generative Processes”,
    Telmo Menezes, Camille Roth, in Dynamics on and of Complex Networks, Volume III: “Machine Learning and Statistical Physics”, eds. F. Ghanbarnejad, R. S. Roy, F. Karimi, J.-C. Delvenne, B. Mitra, Springer Proceedings in Complexity, pp. 83–111
  5. Arnoux T., Tabourier L., Latapy M., “Interaction Prediction Problems in Link Streams” Dynamics On and Of Complex Networks III, pp 135-150, 2019.
  6. Beauvisage T., Mellet K. (à paraître). “ Assetizing and marketizing personal data”, in Birch K, Muniesa F., Turning things into assets. MIT Press.
  7. Cardon (Dominique), « Mapping and measuring reputation: the value of social media metrics », Workhop on value & reputation, Warwick University, London, 4 may 2018. (Communication à paraître dans ouvrage collectif : Stark (David), ed., The Performance Complex: Competition and Valuations in Social Life, Oxford University Presse, 2020)

French journal articles

  1. Dominique Cardon, « Le pouvoir des algorithmes », Pouvoirs, n°164, 2017.
  2. Dominique Cardon, Jean-Philippe Cointet, Antoine Mazières, «La revanche des neurones. L’invention des machines inductives et la controverse de l’intelligence artificielle», Réseaux, n°211, 2018, pp. 173-220
  3. Benbouzid (Bilel), Cardon (Dominique), « Machines à prédire », Réseaux, n°211, 2018, pp. 9-33
  4. Chavalarias, D., Gaumont, N., Panahi, M., 2019. « Hostilité et prosélytisme des communautés politiques ». Réseaux n° 214-215, 67–107.
  5. Cardon (Dominique), Crépel (Maxime), «Algorithmes et régulation des territoires», in Le Galès (Patrick), Courmont (Antoine), Gouverner la ville numérique, Paris, PUF, 2019
  6. Axel Meunier, Donato Ricci, Dominique Cardon et Maxime Crépel, « Les glitchs, ces moments où les algorithmes tremblent », Techniques & Culture, n°72. URL : http://journals.openedition.org/tc/12594
  7. Beauvisage T., Beuscart J.S., Coavoux S., Mellet K., 2019, « Les algorithmes de recommandation musicale et l’autonomie de l’auditeur », Réseaux, n° 213, 1, p. 17‑47.
  8. “Algorithmic Distortion of Informational Landscapes”, Camille Roth, Intellectica, 70(1):97-118, 2019
  9. « Représenter les utilisateurs : le cas des algorithmes de recommandation », Jérémie Poiroux, à paraître dans La vie des idées.

Platforms, software and data

  1. The Politoscope platform on the multipolarity of the French political “twittosphere” during the 2017 presidential elections gathered a significant press coverage. The corresponding iPhone app enables users to access news and filter them by leveraging the data collected and computed by the platform.
  2. A series of three software packages has been produced for the computation of diversity measures according to various definitions, including those introduced by and over the course of the project: triversity and HINpy, respectively an R and a python package to compute general diversity measures (see this paper),  and LogDiv, to compute diversity measures specifically in user navigation logs (see that paper). 
  3. Datasets and code corresponding to the YouTube recommendation graphs collected for “Tubes and Bubbles” (see above) have been made available respectively here and there. Anonymized Facebook ego-centered networks are available here.