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Top 30 Social Network Analysis and Visualization Tools

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We review major tools and packages for Social Network Analysis and visualization, which have wide applications including biology, finance, sociology, network theory, and many other domains.

  • R is a general purpose analytics tool, but several libraries are available for social network analysis. These include degreenet, RSeina, PAFit, igraph, sna network, tnet, ergm, Bergm, hergm, latentnet and networksis. Each provides specialised functionality and for people familiar with R represent a rich set of resources.

  • SocNetV (Social Networks Visualizer) is a cross-platform, user-friendly tool for the analysis and visualization of Social Networks. It lets you construct networks (mathematical graphs) on a virtual canvas, or load networks of various formats (GraphML, GraphViz, Adjacency, Pajek, UCINET, etc). Also, SocNetV enables you to modify the social networks, analyse their social and mathematical properties and apply visualization layouts.


  • Socioviz is a social media analytics platform powered by Social Network Analysis metrics. Allows user to query Twitter conversations and find Identify key influencers, opinions and contents. Social Network graphs (user mention and hashtag copresence) are visualized and can be exported in Gephi format (gexf) for further analysis.

  • Sentinel Visualizer is used for Advanced Link Analysis, Data Visualization, Geospatial Mapping, and SNA. Its database driven data visualization platform lets you quickly see multi-level links among entities and model different relationship types. Advanced drawing and redrawing features generate optimized views to highlight the most important entities.

  • Statnet is a suite of software packages in R for network analysis of the statistical modeling of networks. The analytic framework is based on Exponential family Random Graph Models (ergm). It provides a comprehensive framework for ergm-based network modeling, including tools for model estimation, model evaluation, model-based network simulation, and network visualization. This broad functionality is powered by a central Markov chain Monte Carlo (MCMC) algorithm.

  • SVAT (Smart Visual Analytics Tool) is for data visualization, fraud investigation, and more. It provides user-friendly, cost-effective visualization of links and flows between subjects. A chronological overview of the visualized dataset is crucial in many cases. SVAT supports two different timeline views with a lot of options to choose from. It can mine data from structured or unstructured sources and crunches them to reveal hidden patterns.


  • Tulip is an information visualisation framework dedicated to the analysis and visualisation of relational data. It aims to provide the developer with a complete library, supporting the design of interactive information visualisation. Written in C++ the framework enables the development of algorithms, visual encodings, interaction techniques, data models, and domain-specific visualisations. One of the goal of Tulip is to facilitate the reuse of components and allows the developers to focus on programming their application. This development pipeline makes the framework efficient for research prototyping as well as the development of end-user applications.

  • Visone is a software for the visual creation, transformation, exploration, analysis, and representation of network data, jointly developed at the University of Konstanz and the Karlsruhe Institute of Technology since 2001.the main purpose of the Visone software is to empower researchers in the social sciences to analyze and visualize network data in an integrated fashion. Potential applications range from sociometry to bibliometrics and web analysis.

  • XANALYS specialise in providing powerful software capabilities. From threat assessment, Investigative major case management and advance crime and fraud analytics. It helps to manage multi-jurisdiction major crime investigations, evaluate and analyse suspicious financial transactions, capture and act upon intelligence reports, and disclose evidence in a court-ready format to ensure successful outcomes.