Media, Information Pluralism and Methodological Choices
O.1. Introduction to the theme of digital transformation of media and information pluralism
The debate about information pluralism – a guarantee of a wellfunctioning democracy – is not new. It refers to the issues of freedom and independence of the press, of the sufficient production of varied opinions in line with the different communities of readers, listeners or viewers (Hiller et al. 2015). Traditionally focused on issues of media concentration (Napoli and Gillis 2006; Helberger 2008), the theoretical definition of pluralism includes different elements (Napoli 2001; Benhamou and Peltier 2006; Rebillard 2012a; Napoli and Karppinen 2013): sources (the range of content providers), content (the diversity of the kinds of information or opinions being issued), exposure of individuals to alternative viewpoints and news feeds, variety (the number of news topics covered in a given time period), balance (the distribution of these topics between those that focus attention on the front page and those that are much more isolated) and disparity (the differences in journalistic treatment of the same news topic). Recent work adds other elements, such as the informational richness and added value of online content (Lyubareva et al. 2020).
Overview written by Inna LYUBAREVA and Roger WALDECK.
The various chapters and works cited in this book are part of the research program known as Pluralisme de l’information en ligne (“Pluralism of online information”, or PIL) supported by the French National Research Agency (ANR-17-CE27-0010, 2018-2022).
The current discussions on pluralism take on a new importance due to the digitization of media and contemporary media concentration movements and extend it, a novelty of the digital era, to the intervention of a distinct power: the GAFAMs (Google, Apple, Facebook, Amazon, Microsoft, etc.). They implement different ways of controlling information and conditioning opinions and raise new questions for regulation.
In particular, the development of digital platforms and services has lowered the barriers to entry for the production and distribution of information because of the reduced need for capital needed to create and maintain a newspaper, the increased decentralization of production sources and a sharp reduction in distribution costs. These factors have facilitated the arrival of new entrants and the multiplication of digital business models (Lyubareva and Rochelandet 2016). They also favor new informational practices linked to the ease of accessing, sharing and publishing information online through digital social networks and aggregators. This movement is thus a priori very favorable to information pluralism via the diversification of sources and content, the dissemination of data or the appearance of new forms of journalism.
If such an abundance of content and sources can favor the expression and formation of plural opinions, it is not however synonymous in itself with quality information and, consequently, pluralism. There are many examples and obstacles to quality information, starting with fake news, not to mention the consequences of transformations in the conditions of production (speed-driven journalism1), use (snack content2) and the dissemination of information induced by and subject to the audience data produced by digital platforms and increasingly filtered by their algorithms, and the massive reproduction of content by central agencies such as AP, Reuters and AFP (Paterson 2007; Fenton 2009; Redden and Witschge 2010; Marty et al. 2012; Lyubareva et al. 2020).
This proliferation leads us to rethink the meaning and relevance of information pluralism. We are moving from a situation of scarcity to an abundance of news information, making diversity issues more problematic, which, in a first analysis, would no longer be posed in the same terms (Lyubareva and Rochelandet 2017). The modalities of news selection have evolved: traditionally and until recently, journalists, newsrooms and press
1 That is, journalism focused on the speed of information production.
2 Short and fragmented information that goes straight to the point, “snack content”, often adapted to mobile media and social networks.
institutions have played the role of gatekeepers by filtering news according to professional standards. Although they continue to play this role, with the development of the Internet they are no longer the only ones, and new actors contribute to this selection of information in often different ways: through the provision of search engines, through the use of social media, or through algorithm-based recommendation systems.
Yet these platforms change the rules of the game in order to maximize the value extracted from the use of the proposed services (Cardon 2013). Largely financed by the exploitation of users’ personal data, platforms seem to conform individuals according to their opinions – by exposing them to information that matches their profiles – not offering alternative points of view that are likely to make their opinions evolve and to create debates (see Eli Pariser’s “filter bubble” or Sunstein’s “echo chambers”). These new actors are less concerned with information pluralism (Napoli 2011; Vos and Heinderyckx 2015) than with audience and personal data collection of readers and digital tools; they guide the choices of journalists themselves as to which formats and news topics to cover and which to highlight. Pluralism could thus be affected by the strategies of digital platforms and the redistribution in communication power (Helberger 2011).
Therefore, it is worth questioning to what extent this increase in content is not counterbalanced by a decrease in the pluralism of information being produced, accessed, and consumed (Lyubareva and Rochelandet 2017). A number of theoretical analyses establish important gaps in this area and the urgent need to focus attention on the analysis of information in circulation and its transformative factors (Napoli and Gillis 2006; Karppinen 2009; Napoli 2011). They point out that the notion of pluralism and its evaluation need to be redefined, on the one hand, because the assumption that diversity (as a synonym for quality) is socially desirable needs to be nuanced: it depends precisely on the definitions one chooses (Karppinen 2018) and the underlying conception of democracy (Carpentier and Cammaerts 2006). Approaches to pluralism can thus vary according to the objectives assigned to journalism: informing different readership, promoting public debate and the formation of an informed/enlightened public opinion according to the deliberative democracy model, or fostering the emergence of critical and power-challenging viewpoints with more radical journalism. On the other hand, the notion of pluralism must take into account the relationship between the diversity offered and the diversity consumed (Napoli 2011): does a great
diversity of sources mechanically improve the diversity of content, which in turn, by increasing, would promote the diversity of exposure given that the readership or audience would have more options? Nothing obvious here. Moreover, the supposed diachronic relation between a diversity of “news” offered and a diversity of opinions is not self-evident: more choice of news does not mechanically stimulate more enlightened and more diverse opinions and vice versa. Everything depends on the economic models of the intermediaries of the information market and on the practices of the individuals who can be locked in bubbles (“filter bubbles”, Pariser 2011) or echo chambers (Sunstein 2018) through a structuring operated by social media and personalized recommendation tools contributing to the reduction of sources, interests and opinions of the individuals in spite of the abundance of news.
Finally, there is nothing obvious about the link between the conditions of production (forms of media ownership, journalistic practices, revenue models, etc.) and the characteristics of the information actually produced. The massive adoption of digital tools and uses has led to the emergence of new production practices (new formats, original fact-checking devices, platformization and search for network effects, etc.) and has allowed for the entry of new information producers ranging from pure players3 to the readers themselves, while favoring the entry of new voices (partisan media, independent or activist journalists, etc.). New alternative actors can contribute to increasing the diversity of viewpoints while producing news based on “hearsay” just as traditional reputable news titles can cover a very wide range of topics while multiplying the identical repetition of central agency dispatches (Lyubareva et al. 2020). Alternative forms of financing (crowdfunding, donations) can both contribute to the production of rich and original information and have a negative impact on the disparity of topics covered by the media (Cariou et al. 2017)4. In the same vein, the fact that content is produced by “in-house” journalists does not automatically guarantee its quality. Therefore, the analysis of the link between the conditions of production and the characteristics of the information produced must be part of a detailed empirical study; however, work on this subject remains very rare (Karppinen 2018).
3 A pure player is an information company that uses exclusively digital media for its distribution, without a paper edition.
4 Indeed, too much engagement by reader-contributors can create a new form of dependency for newspaper titles, more than the dependency on advertising revenues.
In summary, the digitization of the media and the current explosion of information content on the Internet highlight the reductive nature of the traditional debate on pluralism, focused mainly on the concentration of capital in the press, and raise new regulatory issues. As a result of these changes, some works on the conceptualization of media pluralism in the current context advocate that studies on this topic should include, beyond the content itself, the economic, social and regulatory dimensions that have proven to be insufficiently addressed by the literature (Van Cuilenburg 2007; Aslama and Napoli 2010; Napoli 2011; Jakubowicz 2015).
For the reasons presented above, the analysis of media and information pluralism in the digital context takes the form of a complex and evolving object of study, calling for a systemic analysis of the different socioeconomic dimensions where the strategies of producers, the informational practices of consumers and the forms of concentration of the written and audiovisual media are articulated to give rise to new issues of pluralism in circulation. The analysis of such an object requires the implementation of appropriate and necessarily varied theoretical and methodological approaches offering an explanatory complementarity of the studied phenomena.
O.2. Methodological choices in social science research on digital transformations
In the social sciences, traditional paradigms are regularly questioned (Kirman 1989, 1992) and the construction of a research project is often accompanied, upstream, by a phase of reflection on the theoretical and methodological frameworks best able to capture new forms of interaction, and the multi-scale dynamics that underlie them. For example, in economics, methodological individualism has long constituted the traditional basis of explanations for industrial phenomena – where any social or economic fact must be understood from the behavior of individuals – implying a reductionism whose extreme representation has been the use of representative agents. In fact, since the Sonnenschein–Mantel–Debreu theorem, the hypothesis of the existence of equilibrium as a stable and single state of the economy is not guaranteed, with the implication that the techniques of comparative statics used by economists are called into question. A strong version of methodological individualism that constructs social facts solely on the basis of egoistic individuals acting under purely
material constraints has been particularly criticized because it neglects a fundamental aspect, that is the structure of interactions (Udehn 2001); it is not so much the nature of individual rationality that influences the nature of emergent properties as the structure of the networks of relations (Granovetter 1985) and at the very least, structural individualism must be at the basis for the understanding of the social facts. Game theory has been an initial response to the integration of interaction structures, however, it remains constrained by aspects linked to the computability of equilibria involving, more often than not, completely random encounters between players, each player having the same chance of meeting any other player. Finally, a methodological individualism that integrates institutional constraints (social norms, legal norms, social preferences, etc.) into the explanation of individual behavior is certainly more representative of the observed social behavior (Camerer et al. 2004; Bowles and Gintis 2011).
Today, the massive diffusion of digital technologies and their uses contributes to the profound transformation of many economic and social activities and is at the origin of the emergence of new industries and sectors. It seems even more difficult to apprehend the growing variety of these mutations from postures based on a strong methodological individualism. Given the increased connectivity and interdependencies between actors and industries, the dynamics propagate at different scales (micro, meso and macro) with multiple feedback loops from micro to macro, and from macro to micro, through interaction structures that are themselves emerging from the effect of individual actions.
One of the important consequences of the associated epistemological approach is that it is necessarily multidisciplinary, as opposed to purely disciplinary research, because it is driven by the object of study, which may represent a market or an industry, a technology or its appropriation, a form of social interaction or an economic model, etc. This multidisciplinarity manifests itself both through the use of varied methodological approaches and through disciplinary cross-fertilizations providing many different points of view on a common object of study. By mutually enriching each other, these cross-disciplinary approaches build interdisciplinary research focused on a common object of study (Morin 1994; Nicolescu 1996).
At the heart of this approach is a fruitful collaboration between different social sciences, but also other disciplines, coming notably from the computational and natural sciences. For example, we can mention the
development, in addition to the hypothetico-deductive approach, which is classical in the social sciences, of an inductive dimension carried out in particular by data analysis based on machine learning techniques. It is therefore important to articulate these theoretical reference frames coming notably from the social sciences with the reality of the field of observation for the formulation of the research problem and hypotheses, and to adapt the methodologies of analysis according to the potential contributions and strength of each of them (using, for example, the anchored method in qualitative analyses or data mining in quantitative studies). The contribution of natural science is particulartly important for the study of the complexity of social systems. Methodologies from statistical physics and evolutionary theories from biology have had an impact in different fields of social sciences, ranging from the study of market dynamics to issues of social and moral dilemmas (Bowles and Gintis 2011). On the other hand, cognitive neuroscience has recently permeated the experimental approaches underlying behavioral economics and psychology in the study of understanding human action (Glimcher and Fehr 2014).
When we talk about the digital context – characterized by actors interacting in instantaneous conditions, new forms of many-to-many communication, an unprecedented pace of innovation affecting new services, formats, uses and modes of production, as well as emerging industries – the adoption of a research approach centered around an object of study to analyze socioeconomic transformations comes up against a certain number of additional epistemological impediments.
For instance, when it comes to the construction of a research project, one of the first and foremost steps is the perimeter definition of the object under analysis, that is, the characteristics and micro-components that structure it, and the transformations that characterize it. This involves answering the following questions: How do we establish the observation period and time measurement? How do we identify the determinants and structuring elements of phenomena when they may be latent or emergent in nature? A lack of attention to these choices can greatly limit the validity of the research results and their generality. The approach can call upon various techniques to extract this information. In this perspective, the availability of big data sources or inductive qualitative approaches may provide, in certain contexts, an advantage for empirically driven approaches over model-driven ones. Furthermore, the definition of the structuring characteristics of the object of study will be influenced by the disciplines that come together to define and
understand it, just as these disciplines will have to agree on the validation of a particular theory or interpretation of data. By way of example, the digital transformations of media and information can be studied from the economic perspective with a focus on business models, from the management and sociological perspectives putting forward new forms of organization and interaction between actors, or from a legal viewpoint with an interest in regulatory mechanisms. Each of these disciplines brings a complementary angle of analysis to the object of study.
In addition, given the extremely rapid pace of innovation and transformation, it seems important to us to deepen the temporal (and spatiotemporal) approach in social science research in general, and on information pluralism in particular. Indeed, in the context of permanent mutations of the technical social systems, a temporal approach allows us to identify and describe, for example, transformations in the economic models of the producers of information, the formation of new public spaces of interaction, the evolution of regulatory devices, etc., and to understand their multi-scale dynamics. On this basis, the modeling of a phenomenon can be possible after the formulation of stylized facts, that is, a “simplified” representation of the world. This modeling approach is particularly useful for predicting certain trends and global evolutionary trajectories in a theoretical manner and for formulating recommendations.
Using the example of media and information pluralism, this book aims to present a variety of methodological approaches that can be applied to other objects of study from the social sciences. Through its different chapters, the book proposes and critically analyses some concrete examples of appropriate methodologies. Our objective is to identify significant methodological issues and avenues of thought, some of which are under-utilized in current social science research.
O.3. Introduction to the chapters in this book
The analysis of media and information pluralism as a complex and evolving research object may require an interdisciplinary openness in order to take into account, in addition to the characteristics of journalistic contents, the new economic constraints, the social interaction mechanisms and forms of discourse, as well as the functioning and specificities of online practices and networked technologies. This book aims at presenting and putting into
perspective different methodological approaches, some of which are well known in the social sciences as well as others which remain in short supply, that have proven their relevance to studies on the different dimensions of media and pluralism. The book is structured into five chapters, each dealing with an approach associated with the analysis of a particular dimension.
Each chapter is devoted to a particular methodology and aims, beyond a general presentation of the principles and reference works, to put into perspective its advantages and limitations for the analysis of the issue of interest. The book will cover a wide range of methods: qualitative methods, agent-based modeling, lexicometric content analysis, social network analysis and the legal approach. Through its different chapters, the book will highlight that the choice of a method is never neutral, neither for the problem under analysis, nor for the results (Waldeck 2019). It will address the question of crossing different methods, as well as the problems that often accompany an openness to interdisciplinarity (Waldeck 2019). In short, it will provide access keys to these different methodologies to an audience of researchers from different social science disciplines. This review of methodological works is built around three key thematic axes of the digital transformation of media and information in circulation, namely (1) the role of online platforms, (2) the new conditions of information production and (3) the legal issues surrounding information pluralism.
Axis 1: Platforms master the function of infomediation by putting Internet users in contact with all types of online information and with other Internet users. An abundant literature has been developed on the functioning of online groups. This work emphasizes the role of platforms that promote the emergence of user communities based on repetitive interactions, a principle of homophily and shared interests (Rheingold 2000; McPherson et al. 2001; Cohendet et al. 2003; Von Hippel 2005). In these collective spaces, users come to occupy a hybrid position between consumers, producers of information and prescribers of opinions. Very often, the socioeconomic analysis of online communities first focuses on a definition of their perimeter, for example, from the point of view of the interests or skills shared by its members (Wenger 1999). Examples include open-source communities where the group’s perimeter is defined within the framework of a project, blogs and wikis with their information production communities and group boundaries defined on the basis of contributions and uses of specific content, or forums of players who share the same passions and interests.
The first two chapters of this book focus on the detection and analysis of new public spaces of interaction within online platforms. In line with the existing literature, it is assumed that user information preferences and, more generally, the diversity of information to which individuals are exposed may be influenced by factors related to sociability, interactivity or a sense of community in addition to the intrinsic characteristics of the information produced by the media.
More precisely, Chapter 1 shows how social network analysis tools allow us to detect a “hidden” aspect of the interactions between platform users, which takes the form of the formation of latent communities, at the interchannel, inter-video or inter-project level, which evolve over time and are likely to orient the users’ information choices, their behaviors and their opinions. Compared to the methodological approaches of existing works, the originality of this approach lies in the detection and analysis of the evolutionary dynamics of interactions within user groups, which are not directly observable at the platform level. This analysis calls for a novel intersection of two methods: social network analysis and community dynamics using data mining. It also discusses how it can be articulated with other tools, such as the discourse analysis of informal language and qualitative methods.
Chapter 2 proposes the agent-based modeling approach to analyze the formation of echo chambers. An agent-based model is a computer model that allows simulation of the actions and interactions of autonomous agents, representing individuals and/or groups of individuals of the real system, in order to understand the behavior of this system. Using an abductive method of iterative process of hypotheses testing, this chapter demonstrates how agent-based simulations permit the identification of factors which have sufficient explaining power for the phenomena of interest. In particular, for the analysis of the echo chambers’ emergence, Chapter 2 tests, among other factors, the convergence of opinions, polarization rate, tolerance of exposure to other opinions and the formation of friendship links on social networks.
Axis 2: A number of studies have evaluated information pluralism through the media bias created by various factors related to market structure, in particular media concentration, with the hypothesis that concentrated markets would produce a variety of news that is suboptimal in relation to demand. On the other hand, preserving competition between press titles,
radio stations or television channels would be more conducive to the production of diversified and quality programs. In the same vein, media revenue models based on advertising are often considered in the literature as representing risks for the pluralism of opinions and information (Anderson and Gabszewicz 2006; Gabszewicz and Sonnac 2006; Garcia Pires 2014). However, few studies are interested in a detailed analysis of the link between, on the one hand, the conditions of production (i.e. the forms of media ownership; their belonging to an institutional category such as national or regional press, pure players, alternative media, etc.; and the economic models on and offline) and, on the other hand, the editorial policy of the media. Such an analysis requires the use of appropriate methods. Chapters 3 and 4 aim to fill this gap by presenting two different methodological approaches, respectively, a sociosemiotic approach and a qualitative analysis by semi-structured interviews.
In order to study the pluralism of sources and journalistic framings in the articles of different types of media, Chapter 3 develops an original research combining qualitative and quantitative methods and crossing the textual analysis of discursive traces with the socioeconomic specificities of the media (periodicity, socioeconomic models, editorial policy). Starting from media categories – national and regional press; print and online publication; daily and periodical periodicity; pure players and news agencies – and various contents (in order to grasp a plurality of information), the semi-automatic approach detailed in this chapter allows an understanding of which types of media often cover events according to the same framings by using the same types of sources.
Chapter 4 focuses on one of the most widely used tools in journalism and news media studies: the semi-structured interview. It puts into perspective the relevance of this classic approach to identify representations of media independence, particularly from the point of view of the business model, and of information pluralism within the different media. This chapter demonstrates how to build a corpus and how to collect relevant discourses from different types of interlocutors: media group managers (CEOs, editorial directors, marketing directors, advertising directors, etc.), editors and journalists. The dynamic approach presented in the chapter begins with the description of data to understand the general environment that frames the production of information, then passes through the sorting and classification stage to structure the corpus, and concludes with the interpretation stage to give meaning to the observations. It contributes to a better understanding of
the objects explored, that is, the perception by the media of pluralism and quality information and the place of these actors in the current media ecosystem.
Axis 3: Finally, the last chapter of this book aims to put into perspective the legal approach to the analysis of media, information and pluralism. The media and the information they produce play a fundamental role in the formation of citizen opinions and the proper functioning of democracies. However, the new practices of economic actors brought about by the advent of the Internet could radically challenge the traditional forms of State intervention, calling for a re-evaluation of public policies and even their redesign through new instruments and the proposal of new forms of regulation. These adaptations require, upstream, an operational definition of information, media and pluralism, that is, through the study of legal sources, the extraction of consensual criteria for the evaluation and regulation of these key concepts. Therefore, Chapter 5 demonstrates why, despite the abundant presence of these concepts in legal and regulatory texts, their characterization and analysis in the field of law are relatively problematic. Is it possible to approach information pluralism and media pluralism as purely legal concepts? This is the methodological question discussed in the last chapter of the book.
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Online Platforms and Analysis of Community Dynamics
1.1. Introduction
Online platforms, such as digital social networks, structure new ways of accessing and circulating digital content. These actors master the function of infomediation via connecting Internet users with any type of online content, but also with other Internet users (Rebillard and Smyrnaios 2010; Rieder and Smyrnaios 2012; Smyrnaios 2017; Heo and Park 2014). The result is the implementation of a “digital” form of audience that marks the shift from an individual consumer to a user inserted and guided by social networks (“socially networked user”; Papacharissi 2010). These networks are structured and evolve within the platform, giving rise to new collective spaces where users come to occupy a hybrid position between consumers, producers of information and content, and prescribers.
The analysis of these social networks is not original in itself. Since the advent of the social web, online community approaches have occupied an important place in socioeconomic research. The first reason is related to the role of digital technologies (Rheingold 2000), which, thanks to their communication functionalities, invite users to build new forms of dialogue of the “many-to-many” type. The second reason is economic and strategic: the repetition of interactions within social groups reduces the risks of opportunistic behavior by economic actors, limits the uncertainties on the behavior of others and contributes, as a result, “to the regulation of markets
Chapter written by Cécile BOTHOREL, Laurent BRISSON and Inna LYUBAREVA
and networks by structuring their organization and by making them more efficient” (Benghozi 2006, author’s translation). Finally, on the consumer side, experience and information sharing helps reduce learning and research costs, and promotes consumer participation in product and service design (DiMaggio and Louch 1998; Von Hippel 2005).
The originality of the approach proposed in this chapter lies in the idea that these interconnected user groups are not always directly observable. They can be formed at the scale of a platform beyond a specific theme, video or channel. Indeed, very often, the socioeconomic analysis of online communities focuses, in an upstream phase, on a definition of their perimeters, for example, from the point of view of the interest or skills shared by its members (Wenger 1999). As an example, we can cite the abundant literature on free software communities, where the perimeter of the group is defined within the framework of a project; blogs or wikis with their information production communities, where the boundaries of the groups are defined on the basis of contributions and uses of specific content; or even forums wherein players share the same passions and interests.
Our work suggests that instead of imposing an a priori perimeter of interaction, an important step in the analysis of social interconnections within digital platforms is to identify the perimeter of these connections. In other words, we hypothesize that connections between actors may emerge in unexpected or hard-to-see parts of platforms and that these connections may have a strong impact on the properties and outcomes of the functioning of online groups and platforms. As a result, the dynamics of evolution and the scale of the actions of these community forms may be as important in the digital context as those of communities and groups previously identified in social science literature.
This perspective highlights the relevance of social network analysis (SNA) tools. Focusing on a structural approach to the relationships between members of an organized social milieu, like a toolbox, SNA makes it possible to visualize and model social relationships as nodes (social actors, individuals, groups or organizations) and links (relationships between these social actors) (Scott 1988; Borgatti et al 2009; Mercanti-Guérin 2010).
SNA designates a set of methods, notions and concepts based on graph theory to study relational phenomena. From a global point of view, the aim is to characterize the whole network (or graph) by quantifying the number of
nodes (or vertices), relations (or edges in graph theory) or the diameter, that is, the longest of shortest paths between each pair of nodes, which gives an indication of the compactness of the graph. The average length of the shortest paths provides an additional indicator of the overall structure of the graph: the lower the average length, the more easily information can flow.
From a local point of view, the aim is to identify singular social actors whose position in the network is remarkable. The measures operated on each node can express either a local centrality (calculated with respect to the neighboring vertices or links, such as the degree) or a global centrality (calculated with respect to the whole graph). The centrality of intermediarity, for example, consists of finding the set of the shortest paths between any pair of nodes passing through a given vertex: the vertices which are most frequently counted in this way are key intermediaries for the circulation of information.
Finally, from an intermediate point of view, SNA allows for the exploration of mesoscopic structures. The identification of densely connected subgroups, called communities, or clusters, is for example essential in the fight against an epidemic.
Therefore, in SNA, the relationships between individuals (the nodes), whatever their nature (discussions, information flow or project funding), are modeled by edges in a graph. In the different contexts of interaction, this graph modeling allows the social network to emerge and to describe its properties at the macro-, meso- or microscopic scale. In contrast to socioeconomic analysis, SNA methods refer to algorithms from machine learning and more generally from data science, which bring out groups of individuals that have dense connectivity. Moreover, these methods are of particular interest to the detection of social interactions that are not directly observable and to understand the emergence and functioning of online communities (e.g. Dupouët et al. 2003).
In this chapter, we will show how SNA enriches the analysis of online platforms via the exploration of interactions taking place within these interaction spaces. We use two examples: the crowdfunding platform Ulule and the social media platform YouTube.
After a brief presentation of our field of study – the Ulule and YouTube platforms – the next two parts focus, respectively, on each of these
platforms. Each part first presents the initial stage of the construction of the social graph. Its structure is determined by the nature and forms of interaction between users on each platform. This is crucial for the following stages of community analysis, both in terms of the choice of analysis methods and the interpretation of the results.
More specifically, in the case of Ulule we highlight that, based on the underlying social graph, a multiplicity of algorithmic methods exist to detect communities. Depending on the choice of an algorithm, the analysis can lead to varied community forms. This choice subsequently necessitates further in-depth study, which is often ignored by socioeconomic works, instead using “ready-to-use” graph tools with certain pre-integrated methods (such as the Gephi tool1).
In the case of YouTube, where the choice of the community detection method is justified by the construction of the interaction graph (the graph containing many connected cliques calling for a particular algorithm appropriate for such a context), our analysis focuses on another technical and conceptual lock: the analysis of community dynamics.
In conclusion, we summarize the interest of SNA methods for the analysis of the different community forms characteristic of online platforms, suggest some avenues of further research and discuss more generally the importance of building a strong interface between social and computer science disciplines in the analysis of digital phenomena.
1.2. Outline: Ulule and YouTube platforms
While very different in terms of their nature and objectives of user interaction, the two examples presented in this chapter – Ulule and YouTube – are among the leading platforms in their respective fields. As such, they represent a particularly interesting field of exploration for us.
Since 2010, Ulule has become one of the leading European crowdfunding sites with more than 2 million members, 24,000 funded projects and a success rate of 63% (in 2018). The choice of the Ulule platform is relevant for our study for two reasons. First, donation crowdfunding, of which Ulule is a part, is highly developed in France. According to data from the watch
1 Gephi.org.
