Katrin Herms just joined the team for three and a half years under the supervision of Camille Roth and within the socsemics ERC project to pursue an interdisciplinary PhD project in sociology linking social network analysis of polarized internet communities with face-to-face Interviews. Linked with her practical background in journalism, her main interests are discourse analysis and social dynamics emerging around political issues in France and Germany.
In 2018, Antoine Mazières and Camille Roth published in Bulletin of Sociological Methodology the article “Large-Scale Diversity Estimation Through Surname Origin Inference”. Recently, Antoine wrote an informal debriefing (in french) of the study, which gives us the chance to make a post on this site.
The abstract of the article is as follow:
The study of surnames as both linguistic and geographical markers of the past has proven valuable in several research fields spanning from biology and genetics to demography and social mobility. This article builds upon the existing literature to conceive and develop a surname origin classifier based on a data-driven typology. This enables us to explore a methodology to describe large-scale estimates of the relative diversity of social groups, especially when such data is scarcely available. We subsequently analyze the representativeness of surname origins for 15 socio-professional groups in France.
Jonas Stein just joined the team for a four-month research internship on user confinement in Twitter networks under the supervision of Camille Roth and Jérémie Poiroux and within the project “SOCSEMICS”. Jonas has a background in agent-based simulation and social network analysis.
More information about him may be found on his LinkedIn profile.
The paper “Tubes and Bubbles – Topological confinement of recommendations on YouTube” by Camille Roth, Antoine Mazières and Telmo Menezes just got published in PLOS ONE.
Contrarily to popular belief about so-called “filter bubbles”, several recent studies show that recommendation algorithms generally do not contribute much, if at all, to user confinement; in some cases, they even seem to increase serendipity [see e.g., 1, 2, 3, 4, 5, 6].
Our study demonstrates however that this may not be the case on YouTube: be it in topological, topical or temporal terms, we show that the landscape defined by non-personalized YouTube recommendations is generally likely to confine users in homogeneous clusters of videos. Besides, content for which confinement appears to be most significant also happens to garner the highest audience and thus plausibly viewing time.
We are opening two doctoral fellowships from September 2020 in the framework of the ANR-funded project RECORDS that is focused on the understanding of practices and dynamics surrounding music streaming platforms.
One fellowship will be based at Géographie-cités in Paris, about the spatial dynamics underlying content consumption on streaming platforms, with music streaming as a primary case study.
The other fellowship will be based at Centre Marc Bloch in Berlin, and will address the large-scale and longitudinal study of algorithmic guidance in the context of music streaming platforms.
Please find the detailed call for application here.
Centre Marc Bloch e.V. is opening a position for a postdoctoral researcher who focus on economic economic and sociological impacts of ICT-related industries. The contract would ideally start on October 1st, 2020 and may cover a maximal period of three years.
Individual research topics could cover the whole field, but a project in one of the four following research directions would be particularly welcome:
- ICT-mediated job markets
- Local markets
- Work automation and algorithmic management
- Emergence of consumers-producers
You may find the detailed Call for Application here.
The team hosts a new ANR-funded grant called “RECORDS” (2020-2023), focused on the understanding of practices surrounding online content platforms, and specifically in the context of musical streaming through a unique partnership with one of the major platforms in this area, Deezer.
The project generally aims at documenting the diversity of practices and behaviors on streaming platforms, understanding the effects of manual and algorithmic content recommendation, and describing the potential spatial diffusion of artists and works. RECORDS articulates quantitative and qualitative empirical protocols, by relying both on a unique source of usage data stemming directly from the platform (comprehensive listening histories on millions of users on several years) and on a large-scale survey (featuring tens of thousands of respondents) and associated interviews with a selection of consenting participants.
The project gathers about 25 researchers of diverse backgrounds including sociology, computer science and geography. It is being supervised byThomas Louail (Géographie Cités), Philippe Coulangeon (Observatoire Sociologique du Changement), Camille Roth (Centre Marc Bloch), Jean-Samuel Beuscart (Orange Labs SENSE) and Manuel Moussallam (Deezer R&D).
The kick-off meeting will take place on two days in June 2020 at the Centre de Colloques of Campus Condorcet in Aubervilliers.
Quentin Villermet just joined the team for a five-month MSc research internship on music recommendation algorithms and their impact on listening practices under the supervision of Camille Roth and Jérémie Poiroux and within the new ANR project “RECORDS”. Quentin has a background in artificial intelligence and his interests include bio-inspired AI, statistics and network infrastructure. More information about him may be found on his LinkedIn profile.
Sunbelt is a the main venue for social network analysis and its 40th edition will take place in Paris in June 2020. As member of the scientific organizing committee, Camille Roth is pleased to announce the call for abstracts, oral presentations and posters. Proposals should be submitted by January 31, 2020 through this link.
Of particular interest to the team is the session “Advances in Socio-Semantic Network Analysis”, led by Iina Hellstein and co-organized by Nikita Basov, Johanne Saint-Charles, Adina Nerghes and Camille Roth. We particularly encourage submissions for this session, whose description follows.
A related session will also also take place during the conference Networks in the Global World (St. Petersburg, July 7-9, 2020): the team further encourages submissions to the “Semantic and Socio-Semantic Networks” session by February 10, 2020.
Sunbelt 2020 session on “Advances in Socio-Semantic Network Analysis”
Social actors (stakeholders, group members, organizations) are linked (or separated) both by their social ties, and the content (knowledge, beliefs, frames, claims) they share (or do not share) in their communication. This interplay between the social relationships and the content of communication is increasingly approached as a socio-semantic network intertwining social and cultural, or cognitive and relational realms, where meanings and interactions coevolve.
This organized session addresses the recent advances in socio-semantic network analysis, and invites theoretical, methodological and empirical papers contributing (but not limited) to the following themes: (1) Theorizing relationships between social structure and meaning structure; (2) Qualitative, quantitative or mixed methods to relate meaning and social relationships; (3) Multivariate socio-semantic networks; (4) Relations between semantic similarity and social ties; (5) Combining relations between stakeholders and their frames; (6) Connecting macro- and micro-level social and semantic network patterns.
Antoine Mazières organizes, along with Élise Marsicano (SAGE), a workshop on Quantification of Discrimination in France. It will take place on March 19, 2020 at the University of Strasbourg (France). The language of the workshop is French. You can submit a proposition of presentation before January 31.
Telmo Menezes had the opportunity to present his last paper with Camille Roth entitled “Automatic Discovery of Families of Network Generative Processes” and published earlier this year [SpringerLink] [arXiv], during an oral session at the Complex Networks 2019 conference in Lisbon.
This work relies on a machine learning approach introduced by them some years ago for automatically discovering plausible and human-understandable generators that fit and help explain observable complex networks. Recently, they expanded this work to identify families of generators, and demonstrated its application in discovering a small number of such families within a large corpus of facebook ego networks. The abstract of the presentation in Lisbon offers a brief overview and can be found here (p. 225), the presentation is here.
The Computational Social Science Team organizes bimonthly internal meetings aimed at discussing “quali-quantitative” approaches. The point of these meetings is to present the work-in-progress carried out within the Pole’s framework and also to offer methodological workshops for training in digital approach (database generation, corpus construction, processing, and so on.). It is thus a forum for dialogue capable of generating new qualitative-quantitative research questions within the Centre Marc Bloch. Please note it will progressively transform into a computational social science seminar open to an outside audience.
In December 2019, we were pleased to listen to:
- Mirjam Dageförde who presented her statistical work (with Emiliano Grossman) about “Selfish, not social! How voters derive their policy preferences”
- Jérémie Poiroux about filter bubbles that Twitter users possibly contribute to build. This work was part of the Algodiv project and will be continued with Camille Roth. The presentation can be found here (in French).
Our paper called “Interactional and Informational Attention on Twitter”, by Agathe Baltzer, Marton Karsai and Camille Roth, just got out in Information 10(8), and is featured on its cover page. This work appraises the distribution of attention at the collective and individual level on Twitter, and both from a social (users) and semantic (topics) viewpoint. We exhibit the existence of socio-semantic attentional constraints and focus effects.
This article by Dominique Cardon, Jean-Philippe Cointet and Antoine Mazières retraces the history of artificial intelligence through the lens of the tension between symbolic and connectionist approaches. From a social history of science and technology perspective, it seeks to highlight how researchers, relying on the availability of massive data and the multiplication of computing power have undertaken to reformulate the symbolic AI project by reviving the spirit of adaptive and inductive machines dating back from the era of cybernetics.
The full english version may be accessed here.
Detailed job offers may be found here with a deadline for application set at September 30th, 2019.
Extensive information on the scientific content and context are available in the above-mentioned job offers – interested applicants may nonetheless feel free to contact Camille Roth (roth[@]cmb.hu-berlin.de) to discuss this further.