Social networks – Data Big and Small

Doctoral thesis: Dynamics of collective elaboration of (in)appropriate information in social networks

We’re hiring!

As part of a large, interdisciplinary European research project, we are seeking a motivated, open-minded student to join CNRS (specifically, the Centre for Research in Economics and Statistics, CREST) in Palaiseau, France, for three years.

The thesis aims to model the production and dissemination of ‘fake news’ in situations of uncertainty and socio-economic inequality. A rich sociological literature suggests that actors contextualise messages received and emitted as questions or answers, interpret them according to their recipients and senders, and assess their social acceptability within their own networks of relationships, taking into account their relative position. Building on this research, the goal is to identify the social processes underpinning misinformation-generating digital communications: collective identity, inequalities of status or authority, hierarchy of shared norms. This will enable interpreting the online social interactions through which actors collectively judge the (appropriate or inappropriate) quality of a message or information and then decide whether to relay or share it – and with whom. In particular, the thesis work will contribute to: 1/ drawing up a state of the art, mainly within sociology but open to the neighbouring disciplines which have also addressed these questions; 2/ illustrating and testing these theories through an empirical analysis of a digital database, mainly with quantitative methods, which may be enriched through a small complementary qualitative fieldwork; 3/ to contribute to the preparation of guidelines that help information professionals and policy-makers to detect the sources and modalities of emergence and propagation of misinformation.

The thesis will be done within the framework of the interdisciplinary project “AI-based-technologies for trustworthy solutions against disinformation” (AI4TRUST), funded by the European Union over the period 2023-2026, involving 17 partners (research institutions and media professionals) in 10 countries, and coordinated by Fondazione Bruno Kessler (Italy).

The AI4TRUST project aims to build a hybrid system, with advanced artificial intelligence solutions capable of cooperating with humans in the fight against disinformation. The new algorithms that will be developed in this framework, constantly checked and improved by human fact-checkers, will monitor multiple online social platforms in nearly real time, analysing text, audio, and visual contents in several languages. The resulting quantitative indicators, including infodemic risk, will be inspected under the lens of social and computational social sciences, to build the trustworthy elements required by media professionals.

CNRS contributes to the study of the sociological dimension of these issues, and participates in the project through its laboratories Centre Marc Bloch (CMB, Berlin), Centre de Sociologie des Organisations (CSO, Paris) and Centre de Recherche en Economie et Statistique (CREST, Palaiseau). In practice, the thesis will be carried out at CREST, and co-directed by representatives of the three laboratories involved in this AI4TRUST: myself, Emmanuel Lazega (CSO) and Camille Roth (CMB).

The successful candidate will have the opportunity to join a group of highly motivated scientists and practitioners from across the continent; to participate in collaborations with other teams working on the project in an interdisciplinary framework; to attend regular meetings with the project’s principal Investigator, the scientists and experts involved, and public decision-makers; to present and publish research results in international conferences and journals.

The ideal candidate has a good background in quantitative sociology or in a STEM discipline (e.g., mathematics, statistics, computer science) with a strong interest in societal issues and challenges. A very good knowledge of English, an interdisciplinary approach and the ability to work in teams are essential.

Candidates should apply on the CNRS portal, where they will also find more details.

Pathways in Network Science

I’m happy and honoured to speak today at the “Pathways in Network Science” online seminar of the Women in Network Science (WiNS) group.

Pathways in Network Science aims to give the stage to women and nonbinary researchers in network science to share their career paths or some pertinent aspects of it. Presentations can be a summary of the research topics explored along a speaker’s career path or even an autobiographical presentation about how opportunities and challenges influenced her aspirations and impacted her career path. It can also include discussing gender-related challenges and experience with individual strategies and/or systemic changes.

I’ll talk about myself in terms of mobility – both geographic and disciplinary – and the challenges and opportunities it represented. I’ll also talk about resilience – or how network science helped me to make true my dream of devoting my life to research. I’ll mention impact – or how to think of the place of science in society, and how network research can lead to positive change. I’ll conclude with the challenges ahead – and how they are not only scientific, but also deeply human and social.

Hidden inequalities: the gendered labour of women on micro-tasking platforms

Around the world, myriad workers perform data tasks on online labour platforms to fuel the digital economy. Mostly short, repetitive and little paid, these so-called ‘micro-tasks’ include for example labelling objects in images, classifying tweets, recording utterances, and transcribing audio files – notably to satisfy the data appetite of today’s fast-growing artificial intelligence industry. While casualization of labour and low pay have attracted sharp criticisms against these platforms, they appear gender-blind and accessible even to people with basic skills. Women with care or household duties may particularly benefit from the time flexibility and the possibility to work from home that platforms offer. So, are these new labour arrangements gender equalizers after all?

In a new paper co-authored with Marion Coville, Clément Le Ludec and Antonio A. Casilli, we demonstrate that this new form of online labour fails to fill gender gaps, and may even exacerbate them. We proceed in three steps. First, we show that legacy inequalities in the professional and domestic spheres turn platform-mediated micro-tasking into a ‘third shift’ that adds to already heavy schedules. Both working fathers and working mothers experience it, but the structure of the other two shifts affects their experience. Looking at their time use, it turns out that men dedicate long and uninterrupted slots of time to each activity: their main job, their share of household duties, leisure and micro-work. They tend to do all micro-tasks in a row, usually at night after work or in the morning before starting. Instead, women have more fragmented schedules, and micro-work during short breaks, here and there, eating into their leisure time. This is one reason why they earn less on platforms: they have short slots of time available, so they cannot search for better-paid tasks, and just content themselves with whatever is available at that moment.

Time use of typical female (left) and male (right), micro-workers, both of whom have a main job in addition to platform micro-tasks, and dependent children.

Second, we submit that the human capital of male and female data workers differ, with women less likely to have received training in science and technology fields.

Highest educational qualification (left) and discipline of specialization (right) of men and women micro-workers. Data collected in France, 2018 (n = 908).

Third, their social capital differs: using a position generator instrument to capture workers’ access to the informational and support resources that may come from contacts with people in different occupations, we show that women have fewer ties to digital-related professionals who could provide them with knowledge and advice to successfully navigate the platform world.

Gender assortativity index for each occupation in the 48-item position generator that measures respondents’ social capital. Each panel represents respondents’ choices, ordered from lowest (negative) to highest (positive) degree of similarity. Top panel: female respondents, bottom panel: male respondents. The bars corresponding to digital and computing occupations are hatched.

Taken together, these factors leave women with fewer career prospects within a tech-driven workforce, and reproduce relegation of women to lower-level computing work as observed in the history of twentieth-century technology.

The full paper is available in open access here.

It is part of a full special issue of Internet Policy Review on ‘The gender of the platform economy‘, guest-edited by M. Fuster Morell, R. Espelt and D. Megias.

The visualization of personal networks

I am pleased to co-organize with Vincent Lorant of UCLouvain a special session on “The visualization of personal networks” at the forthcoming INSNA Sunbelt conference (12-16 July 2022, Cairns, Australia, and online).

Personal network data collection methods allow describing the composition and the structure of an individual’s (hereafter ego) social network. This method has been implemented in different domains such as migration, drug use, mental health, aging, education, and social welfare. Over the last years, these data have also been used to provide respondents with visualizations of their personal network, using different algorithms and customizing results through computer assisted data collection. Visualization gives valuable feedback to the respondent, improves data validity and may trigger positive behavioural changes, notably in vulnerable individuals or groups. Yet, visualization is not a free lunch. Recent research has evidenced the ethical dilemmas of providing such feedback to individuals: ego’s social life is being exposed, the researcher may be exposed as well, and such feedback may imply some contractual exchanges or therapeutic implications that require attention.

This session aims to describe the stakes of different visualization approaches to personal networks with different populations. We welcome qualitative and quantitative papers addressing issues related to the implementation of visualization or reports of personal networks in terms of techniques, levels of respondent’s satisfaction with visualization, conditions under which visualization is recommended or discouraged, and effects of the personal network visualization for the respondent.

More information on the conference and the submission process is available here.