Network science gathers methods coming from various disciplines which sometimes hardly cross the boundaries between these disciplines. Widely used in molecular biology in the study of protein interaction networks, the enumeration, in a network, of all possible subgraphs of a limited size (usually around four or five nodes), often called graphlets, can only be found in a few works dealing with social networks. In the present work, we apply this approach to an original corpus of about 10,000 non-overlapping Facebook ego networks gathered from voluntary participants by a survey application. To deal with so many similar networks, we adapt the relative graphlet frequency to a measure that we call graphlet representativity, which we show to be more effective to classify random networks having slight structural differences. From our data, we produce two clusterings, one of graphlets (paths, star-like, holes, light triangles, and dense), one of networks. The latter is presented with a visualization scheme using our representativity measure. We describe the distinct structural characteristics of the five clusters of Facebook ego networks so obtained and discuss the empirical differences between results obtained with 4-node and 5-node graphlets. We also provide suggestions of follow-ups of this work, both in sociology and in network science.

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Cet article décrit la diversité des comportements sur Facebook. À partir d'une enquête quantitative portant sur les données extraites de 15 145 comptes Facebook, il propose une interprétation morphologique et structurale des modalités d'expression et interaction sur le réseau socionumérique. Six configurations sont identifiées à partir des différentes activités que la plateforme offre aux utilisateurs : une classe de non-actifs, deux classes dominées par la conversation (en groupe, ou distribuée sur la page des amis) et trois classes d'utilisateurs qui privilégient l'expression sur leur propre page (égocentrés, égovisibles, partageurs). En croisant ces données d'activité avec des indicateurs socio-démographiques ou structurels, on saisit l'influence capitale de l'âge, du sexe ou de la structure du réseau amical sur ces configurations. On observe ainsi une forte sensibilité du réseau en fonction de l'âge de l'utilisateur et une spécialisation d'un sous-réseau de commentateurs réguliers chez les utilisateurs les plus actifs de Facebook. What do we do on Facebook? Activity patterns and relational structures on a social network Abstract: This article describes various configurations of activities on Facebook. We rely on a quantitative survey over 15,145 Facebook users to propose a morphological and structural interpretation of user behavior on online social networks. Six configurations are identified from the traces of the various possible activities on Facebook: Non-active users, two configurations dominated by conversation (in groups or distributed on the pages of Facebook Version preprint

There is a growing interest in how data generated in learning platforms, especially the interaction data, can be used to improve teaching and learning. Social network analysis and machine learning methods take advantage of network topology to detect relational patterns and model interaction behaviors. Specifically, small induced subgraphs called graphlets, provide an efficient topological description of the way each node is embedded in the meso-scale structure of a network. Here we propose to detect the roles occupied by the different participants, students and teachers, in the successive phases of courses modeled by a sequence of static snapshots. The detected positions, obtained thanks to graphlet enumeration combined with a clustering method, reveal the different roles observed in each snapshot. We also track the role changes through the overall sequence of snapshots. We apply our method to the Sqily platform and describe the mutual skill validation process. The detected roles, the transitions between roles and a overall visualization through Sankey diagrams help interpreting the course dynamics. We found that some roles act like necessary steps to engage students within an active exchange process with their classmates.