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.
This week, I was pleased and honoured to give a keynote speech at wonderful EUSN2021 (European Social Networks 2021) conference. The event was originally planned in beautiful Naples, but was unfortunately moved online because of pandemic-induced uncertainties.
In my talk, I endeavoured to reconcile the tradition of research on social and organizational network analysis – in which I have been trained, and which constitutes the specialism of most participants to EUSN conferences – with the nascent literature on digital platform labour. Indeed, organizational network studies have shaped my (and many other colleagues’) understanding of how social ties and structures drive collective action and shape its outcomes. However, contemporary computing technologies breed novel sociabilities and organizational modes that disrupt established practices and knowledge. In particular, the emergence of digital platforms as market intermediaries constitutes a puzzle for network researchers. These emerging organizational structures loosen individual-organization links, fragment production processes, individualize sub-contracting, extend competition beyond the local level, and threaten jobs with AI-fuelled automation. My question then is: in these environments where isolation dominates and collaboration fades, how do social networks operate, if at all? And how can we, as researchers, apprehend them?
In my talk, I discussed how digital platforms, and the transformations of work processes they trigger, challenge some of the key tenets of organizational network analysis. Yet there is still much to learn from this tradition, and the limited overlaps with the nascent literature on platforms reveal facets that neither of them, alone, could capture. This analysis also confirms that overall, technology-enabled platform intermediation restrains sociability and limits interactions, but specific cases where networking has been possible highlight the fundamental advantages it brings to workers.
On this basis, I outlined directions for future research and policy action.
Many thanks to the organizers who still did a wonderful job despite the online-only mode, and to all attendees for inspiring questions and feedback.
Research on social networks raises formidable ethical issues that often fall outside existing regulations and guidelines. State-of-the-art tools to collect, handle, and store personal data expose both researchers and participants to new risks. Political, military and corporate interests interfere with scientific priorities and practices, while legal and social ramifications of studies of personal ties and human networks come to the surface.
The proposed special section aims to critically engage with ethics in research related to social networks, specifically addressing the challenges that recent technological, scientific, legal and political transformations trigger.
Following a successful workshop on this topic that was held in December 2017 in Paris, we welcome submissions that critically engage with ethics in research related to social networks, possibly based on reflective accounts of first-hand experiences or case studies, taken as concrete illustrations of the general principles at stake, the attitudes and behaviors of stakeholders, or the legal and institutional constraints. We are particularly interested in novel, original answers to some unprecedented ethical challenges, or the need to reinterpret norms in ambiguous situations.
As part of the upcoming NetSci2018 conference in Paris, I co-organize a satellite event that aims to foster interdisciplinary reflection on how methods from social science can be upscaled to large network structures and on how methods from complex systems can be downscaled to deal with small heterogeneous structures.
The idea is to reconcile two traditions of research that have remained separate so far. Sociology typically handles small but rich networks where a wealth of network attributes results from the complexity of the data collection design. Differences across nodes and edges enable to capture the social processes underlying network structures and their dynamics. Instead, the complex systems tradition handles large but poorly-specified networks. Assuming statistical equivalence of graph entities, a mean field treatment suffices to describe the aggregate properties of the network. Today’s network data-sets contain an unprecedented quantity of relational information within and between all possible levels: individuals, social groups, organizations, and macro entities. Such large and rich network structures expose the implicit limitations of the two above-mentioned approaches: classical sociological methods cannot be upscaled because of their heavy algorithms, and those from complex systems lose track of the multi-faceted nature of social actors, their relationships and their processes.
Our satellite event aims to move forwards, inviting an inter-disciplinary reflection and exploring ways in which these limitations can be overcome.
Research on social networks is experiencing unprecedented growth, fuelled by the consolidation of network science and the increasing availability of data from digital networking platforms. However, it raises formidable ethical issues that often fall outside existing regulations and guidelines. New tools to collect, treat, store personal data expose both researchers and participants to specific risks. Political use and business capture of scientific results transcend standard research concerns. Legal and social ramifications of studies on personal ties and human networks surface.
We invite contributions from researchers in the social sciences, economics, management, statistics, computer science, law and philosophy, as well as other stakeholders to advance the ethical reflection in the face of new research challenges.
The workshop will take place on 5 December 2017 (full day) at MSH Paris-Saclay, with open keynote sessions to be held on 6 December 2017 (morning) at Hôtel de Lauzun, a 17th century palace in the heart of historic Île de la Cité.
Let us know if you wish to be panel discussant or session chair by 20 October 2017 (send to: email@example.com).
Acceptance notifications will be sent by 31 October 2017.
Registration is free but mandatory: speakers (and discussants and chairs) should register between 15 October and 15 November 2017, other attendees by 30 November 2017.
José Luis Molina, Autonomous University of Barcelona, “HyperEthics: A Critical Account” Bernie Hogan, Oxford Internet Institute, “Privatising the personal network: Ethical challenges for social network site research”
Antonio A. Casilli (Telecom ParisTech, FR), Alessio D’Angelo (Middlesex University, UK), Guillaume Favre (University of Toulouse Jean-Jaurès, FR), Bernie Hogan (Oxford Internet Institute, UK), Elise Penalva-Icher (University of Paris Dauphine, FR), Louise Ryan (University of Sheffield, UK), Paola Tubaro (CNRS, FR).
Each speaker briefly presented a case study that involved visualization, and all were great in conveying exciting albeit complex ideas in a short time span. What follows is a short summary of the main insight (as I saw it).
Online health communities have been demonstrated to be an important part of the self-empowering experience of today’s patients. While most attention so far has been devoted to self-styled health communities, where patients autonomously share expertise and experience, today policymakers and healthcare providers are harnessing the power of this very idea and are offering similar solutions themselves.
Earlier this week at the OuiShare Fest Barcelona – a major get-together of the Spanish-speaking collaborative economy community in Europe – a few of these initiatives were presented.
Social Diabetes is a small company founded by and for patients, that offers a mobile app for online, real-time health monitoring services. Diabete sufferers can use it to optimally adjust their insulin dosage based on their carb count and blood sugar levels; in some cases, they can also track their exercise and patterns of behavior to receive alerts whenever relevant. Patients can share this information with their doctors, also through the app; and can discuss with other patients. This is an example of a user-based innovation where autonomous patients take the initiative, aiming to take control of their health and life. Still, physicians have been allowed in: the platform has a medical advisory board, and individual doctors can register as users to follow their patients.
The rise of digital data, particularly data from the internet, is to be understood in social relational perspective. Online interactions – from email exchanges to use of VOIP services and participation in social media such as Facebook, Twitter and LinkedIn – make people’s social connections explicit and visible. The “social network”, once a metaphor used only in a small sub-field within sociology, is now familiar to everybody as the archetype of computer-mediated social interaction. Digital devices systematically record network structures, so that social ties become an essential part of every individual profile, and users are more and more aware of them.
One consequence of this is the booming popularity of network analysis concepts, which support the algorithms that handle digital data: for example, centrality measures are at the heart of search engine functionalities, and transitivity measures found “friend-of-a-friend” algorithms in social media. In passing, social network analysis itself which had been originally developed for small-sized, non-digital datasets (like surveys about friendship in schools) has undergone a major upgrade to account for social data from the web.
More importantly, the relational nature of digital data and the underlying possibilities to use social network analysis, open up new avenues for data collection. If user B publishes a post on, say, their Facebook wall, comments and “likes” received from their friends A, D and E will be connected to the profile of B, accessible and visible from it; in other words, it is possible to retrieve information on A, D or E through the profile of just B. In general social networks, a friend of my friend is my friend; in digital networks, the data of my friends are my data.
Last June, a group of Italian MPs proposed jail terms and fines for authors of so-called “pro-ana” (anorexia) and “pro-mia” (bulimia) websites. These are self-styled online communities on eating disorders which are viewed as promoting extreme dieting and unhealthy eating practices. France and the United Kingdom preceded Italy’s attempt to pass restrictive legislation as far back as 2008-9, and many internet service providers also endeavoured to ban these contents.
But the potential spread of health-hazardous behaviours is probably only one side of the coin, and these websites might also channel health-enhancing assistance, advice, and support (Yeshua-Katz & Martins 2013). In fact a closer look reveals that website users carefully manage their online socialisation to address their health challenges. Online social spaces enable discussion around the illness and constitute a complement, albeit an admittedly imperfect one, to formal healthcare services. There is no rejection of standard health norms in the name of some extreme ideal of thinness but rather a need – or perhaps, a cry – for extra support.
A social science approach brings out these results. The effect of web interactions on health does not only depend on website contents, but also on how people actually use them, share them, and access resources through them. The social, rather than just clinical dimension of eating disorders, recognized long before the advent of the web (Bell 1985, Orbach 1978), becomes ever more relevant in the current context and calls for a more comprehensive view of the “ana” and “mia” social universe.
How many people do you know? How many friends do you have? You may have tried to count your contacts on Facebook or other social networking websites. You may even have felt a bit weird realizing that your “real” friends — those you can rely on — are just a handful. As unexpected it might seem, business professionals have this question in mind too: they want to get a sense of the potentially useable social capital of their associates and employees.
Social research has investigated this matter intensely and can offer insight. There are, in fact, two aspects to be considered: the size of personal networks and the effects of online communication on socialisation.
The size of personal networks
Let us first start with the size of personal networks. A milestone in this debate is the so-called “Dunbar’s number“, based on a 1992 study of Oxford anthropologist Robin Dunbar. The idea is that human cognitive capacities as measured by the size of the neocortex lead to a network size of around 148 (with some range of variation). The original study compared the size of the neocortex in various groups of primates and humans and referred to cohesive communities. The resulting limit indicates the number of people with whom one can maintain “stable” social relationships, i.e., know who each contact is, and how they are related to one another.
Other parts of the brain may be involved too, suggest neuroscientists: Lisa Barrett and her co-authors (2010) found a correlation between amygdala volume and social network size in humans. (I understand that the amygdala is the part of brain that regulates emotional responses and aggression, while the neocortex to which Dunbar referred is the part of the brain that presides higher mental functions.) (see this Blogpost for further information).
In social network analysis perspective, it is also important to define which social network we are measuring. Peter Marsden (1987) distinguished “core” networks from whole personal networks, pointing out that even when people have many friends, there are only a handful with whom they “can discuss important matters”. In this sense, core networks may not include more than five or six people. So if you thought you had very few friends, you shouldn’t feel weird after all… apparently the Portuguese have a saying, “You have five friends, and the rest is landscape.”
On the other hand, your full network also including mere acquaintances and weaker ties may be much larger than Dunbar’s: counts of full networks taken by Peter Killworth, H. Russel Bernard, Chris McCarthy and co-authors in the 1990s – 2000s went up to about 1500 for the average American. From these, they extracted more meaningful measures of networks that are really relevant for people’s daily lives and came up with other numbers: they found a mean personal network size of 290 (twice the Dunbar number!); more recently, Matthew Salganik and his co-authors (2010) have come up with an even larger size of 610 (twice Killworth’s number…).
Overall, an issue that emerges from many of these discussions is that cognitive capacities (however defined) matter primarily because they are associated with a basic limitation of all living beings –time is finite. Therefore, increasing the size of one’s personal network implies that less time is available for each contact: the size of the overall network increases, but the size of the core network doesn’t. Weak ties may gain at the expense of strong ties.