Sébastien Heymann's research while affiliated with Sorbonne Université and other places
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Publications (16)
Gephi is a network visualization software used in various disciplines (social network analysis, biology, genomics…). One of its key features is the ability to display the spatialization process, aiming at transforming the network into a map, and ForceAtlas2 is its default layout algorithm. The latter is developed by the Gephi team as an all-around...
Complex networks
may be studied in various ways, e.g., by analyzing the evolutions of their topologies over time, and in particular of their community structures. In this paper, we focus on another type of dynamics, related to diffusion processes on these networks. Indeed, our work aims at characterizing network dynamics from the diffusion point of...
Social bookmarking systems have recently received an increasing attention in both academic and industrial communities. This success is owed to their ease of use that relies on a simple intuitive process, allowing their users to label diverse resources with freely chosen keywords aka tags. The obtained collections are known under the nickname of Fol...
This paper describes the design of Knot, a digital tool for exploring historical social networks, developed within a multidisciplinary research context involving designers, humanities scholars and computer scientists. The goal of the tool is to provide scholars and researchers with an environment for exploring multi-dimensional and heterogeneous da...
Diffusion phenomena occur in many kinds of real-world complex networks, e.g., biological, information or social networks. Because of this diversity, several types of diffusion models have been proposed in the literature: epidemiological models, threshold models, innovation adoption models, among others. Many studies aim at investigating diffusion a...
Platforms which combine data mining algorithms and interactive visualizations play a key role in the discovery process from complex networks data, e.g. Web and Online Social Networks data. Here we illustrate the use of Gephi, an open source software for networks visual exploration, for the visual analysis of Business Intelligence data modeled as co...
How should we characterize the dynamics of the Web? Whereas network maps have contributed to a redefinition of distances and space in information networks, current studies still use a traditional time unit -the second- to understand the temporality of the Web. This unit leads to the observation of exogenous phenomena like day-night patterns. In ord...
Monitoring the evolution of user-system interactions is of high importance for complex systems and for information systems in particular, especially to raise alerts automatically when abnormal behaviors occur. However current methods fail at capturing the intrinsic dynamics of the system, and focus on evolution due to exogenous factors like day-nig...
Monitoring the evolution of user-system interactions is of high impor- Tance for complex systems and for information systems in particular, especially to raise alerts automatically when abnormal behaviors occur. However current methods fail at capturing the intrinsic dynamics of the system, and focus on evolution due to exogenous factors like day-n...
Finding outliers in datasets is a classical problem of high interest for (dynamic) social network analysis. However, most methods rely on assumptions which are rarely met in practice, such as prior knowledge of some outliers or about normal behavior. We propose here Out skewer, a new approach based on the notion of skewness (a measure of the symmet...
Creating an efficient, interactive and flexible unified graph visualization system is a difficult problem. We present a hardware accelerated OpenGL graph drawing engine, in conjunction with a flexible preview package. While the interactive OpenGL visualization focuses on performance, the preview focuses on aesthetics and simple network map creation...
Gephi is an open source software for graph and network analysis. It uses a 3D render engine to display large networks in real-time and to speed up the exploration. A flexible and multi-task architecture brings new possibilities to work with complex data sets and produce valuable visual results. We present several key features of Gephi in the contex...
Gephi is an open source software for graph and network analysis. It uses a 3D render engine to display large networks in real-time and to speed up the exploration. A flexible and multi-task architecture brings new possibilities to work with complex data sets and produce valuable visual results. We present several key features of Gephi in the contex...
Citations
... The network analysis was performed in R with the Hmisc package and visualized through Gephi (version 0.9.2; https://g ephi.org/; Bastian et al., 2009;Harrell, 2019). Briefly, the correlations between ARG copy numbers and the abundance of MRGs and pathogens were determined through the Spearman method, and the Benjamini-Hochberg (BH) method was used to correct the P values. ...
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... We will observe how the different communities we measure may reflect this division. Communities of this episode are illustrated in Figs. 8 and 9 and with Gephi (Heymann 2014) for SW3 only, all other episodes are also illustrated in the Additional file 1. ...
... 'grafos'), such as 'Gephi' (www.gephi.org)-data visualization and exploration software (Heymann, 2014). Graph-of-word was utilized, as it is a type of visualization that generates a graph representation of texts by considering the order and distance of the words (Skianis, Rousseau, & Vazirgiannis, 2016). ...
... De plus, ces di érences nous permettent d'évaluer la pertinence de notre dé nition du temps intrinsèque au regard de la dynamique du graphe. Ces travaux ont été publiés dans [Albano, 2011], [Albano et al., 2012], [Albano et al., 2013] et [Albano et al., 2014a]. ...
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... Websites such as Sourceforge or Github have provided a privileged field for such studies. In this field, bipartite graphs are used to study technology adoption [18], information diffusion between different projects [41], to predict future engagement of developers to new projects [42] or to identify patterns of interaction between users and Web sites [43]. ...
... The tool is a code notebook written in Javascript [10] that loads scholars' data from a GitHub repository and produces semi-昀椀nished visualizations in the format of editable vectorial images. The semi-昀椀nished visualizations employ force-based spatialization algorithms (Jacomy et al., 2014) [11] to position the nodes of the network and employ a consistent part of the visual encoding. Since they visually exposed for the 昀椀rst time the data and the structure of the ontology, they allowed scholars to identify and 昀椀x inaccuracies in data, like the lack of metadata for certain nodes. ...
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... i) a static graph is constructed from a multigraph that is generated using the configuration model [80] and deleting the duplicate links and self-links ii) an active interval is generated for each link when contacts can occur i.e. nodes are present in the graph. The duration of active intervals is generated using a truncated power-law. ...
... The distribution of the output power is highly right-skewed, as is illustrated in Figure 5(A). Asymmetry is measured by skewness [31] to explain the deviates from the normal distribution. To compute the skewness of the data, the Equation 2 is given: ...
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... This account, which has 11.9 million followers, uploaded a video that had reached 109,460 views as of June 16, 2022, with 288 comments coming in. The author conducted data collection on June 16, 2022.The Gephi 0.9 software analyzes network visualization and centrality calculations with the Yifan Hu proportional algorithm layout with degree ranking criteria because it presents data neatly and informatively in visualizing relationships between actors, determining characters, and central nodes[35] [36] [5][37]. ...
... The interactive tools are designed to work together to help reveal many types of connectedness by facilitating multiple different points of view combined with faceting and filtering on different dimensions of the data. It is assumed that no one view is complete, but that a more complete picture is understood as much by seeing what is missing as by seeing the extant data (see Rendgen & Weidemann, 2012: 155;Uboldi et al., 2013). An exploration of Lombardi's data set with Palladio, for example, might begin with a map of the known locations. ...
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