ForceAtlas2, a Continuous Graph Layout Algorithm for Handy Network Visualization Designed for the Gephi Software
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{"title"=>"ForceAtlas2, a continuous graph layout algorithm for handy network visualization designed for the Gephi software", "type"=>"journal", "authors"=>[{"first_name"=>"Mathieu", "last_name"=>"Jacomy", "scopus_author_id"=>"36056367900"}, {"first_name"=>"Tommaso", "last_name"=>"Venturini", "scopus_author_id"=>"15849341500"}, {"first_name"=>"Sebastien", "last_name"=>"Heymann", "scopus_author_id"=>"55605513700"}, {"first_name"=>"Mathieu", "last_name"=>"Bastian", "scopus_author_id"=>"56208964500"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "arxiv"=>"arXiv:1209.0748v1", "scopus"=>"2-s2.0-84902603261", "sgr"=>"84902603261", "pui"=>"373337813", "isbn"=>"10.1371/journal.pone.0098679", "pmid"=>"24914678", "doi"=>"10.1371/journal.pone.0098679"}, "id"=>"beb65b25-461b-3f0b-9e7d-28b7215e32b5", "abstract"=>"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 solution to Gephi users' typical networks (scale-free, 10 to 10,000 nodes). We present here for the first time its functioning and settings. ForceAtlas2 is a force-directed layout close to other algorithms used for network spatialization. We do not claim a theoretical advance but an attempt to integrate different techniques such as the Barnes Hut simulation, degree-dependent repulsive force, and local and global adaptive temperatures. It is designed for the Gephi user experience (it is a continuous algorithm), and we explain which constraints it implies. The algorithm benefits from much feedback and is developed in order to provide many possibilities through its settings. We lay out its complete functioning for the users who need a precise understanding of its behaviour, from the formulas to graphic illustration of the result. We propose a benchmark for our compromise between performance and quality. We also explain why we integrated its various features and discuss our design choices.", "link"=>"http://www.mendeley.com/research/forceatlas2-continuous-graph-layout-algorithm-handy-network-visualization-designed-gephi-software", "reader_count"=>448, "reader_count_by_academic_status"=>{"Unspecified"=>12, "Professor > Associate Professor"=>17, "Librarian"=>5, "Researcher"=>71, "Student > Doctoral Student"=>27, "Student > Ph. D. 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Student"=>120, "Student > Postgraduate"=>22, "Student > Master"=>94, "Other"=>19, "Student > Bachelor"=>33, "Lecturer"=>7, "Lecturer > Senior Lecturer"=>2, "Professor"=>19}, "reader_count_by_subject_area"=>{"Unspecified"=>26, "Agricultural and Biological Sciences"=>51, "Arts and Humanities"=>14, "Philosophy"=>1, "Business, Management and Accounting"=>13, "Chemistry"=>4, "Computer Science"=>130, "Decision Sciences"=>5, "Earth and Planetary Sciences"=>4, "Economics, Econometrics and Finance"=>12, "Energy"=>1, "Engineering"=>34, "Environmental Science"=>15, "Biochemistry, Genetics and Molecular Biology"=>8, "Mathematics"=>7, "Medicine and Dentistry"=>17, "Design"=>3, "Neuroscience"=>2, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Physics and Astronomy"=>9, "Psychology"=>14, "Social Sciences"=>71, "Immunology and Microbiology"=>2, "Linguistics"=>4}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>17}, "Social Sciences"=>{"Social Sciences"=>71}, "Decision Sciences"=>{"Decision Sciences"=>5}, "Physics and Astronomy"=>{"Physics and Astronomy"=>9}, "Psychology"=>{"Psychology"=>14}, "Mathematics"=>{"Mathematics"=>7}, "Unspecified"=>{"Unspecified"=>26}, "Environmental Science"=>{"Environmental Science"=>15}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}, "Arts and Humanities"=>{"Arts and Humanities"=>14}, "Design"=>{"Design"=>3}, "Engineering"=>{"Engineering"=>34}, "Chemistry"=>{"Chemistry"=>4}, "Neuroscience"=>{"Neuroscience"=>2}, "Energy"=>{"Energy"=>1}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>4}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>12}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>2}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>51}, "Computer Science"=>{"Computer Science"=>130}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>13}, "Linguistics"=>{"Linguistics"=>4}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>8}, "Philosophy"=>{"Philosophy"=>1}}, "reader_count_by_country"=>{"Hungary"=>1, "United States"=>11, "Japan"=>2, "United Kingdom"=>4, "Malaysia"=>1, "India"=>1, "Spain"=>6, "Canada"=>4, "Netherlands"=>4, "Ireland"=>1, "Finland"=>3, "Denmark"=>2, "Poland"=>1, "Brazil"=>2, "Italy"=>2, "Australia"=>3, "France"=>5, "Germany"=>2, "Estonia"=>2}, "group_count"=>32}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1529049"], "description"=>"<p>Layouts with Fruchterman-Reingold (), ForceAtlas2 () and the LinLog mode of ForceAtlas2 ().</p>", "links"=>[], "tags"=>["data visualization", "Infographics", "graphs", "Network Analysis", "social networks", "software engineering", "Software tools", "mathematics", "Applied mathematics", "algorithms", "Sociology", "communications", "semiotics", "types"], "article_id"=>1052521, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Mathieu Jacomy", "Tommaso Venturini", "Sebastien Heymann", "Mathieu Bastian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098679.g001", "stats"=>{"downloads"=>3, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Layouts_with_different_types_of_forces_/1052521", "title"=>"Layouts with different types of forces.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-10 03:24:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/1529050"], "description"=>"<p>Fruchterman-Rheingold layout on the left (regular repulsion) and ForceAtlas2 on the right (repulsion by degree). While the global scheme remains, poorly connected nodes are closer to highly connected nodes. ().</p>", "links"=>[], "tags"=>["data visualization", "Infographics", "graphs", "Network Analysis", "social networks", "software engineering", "Software tools", "mathematics", "Applied mathematics", "algorithms", "Sociology", "communications", "semiotics", "repulsion"], "article_id"=>1052522, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Mathieu Jacomy", "Tommaso Venturini", "Sebastien Heymann", "Mathieu Bastian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098679.g002", "stats"=>{"downloads"=>2, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Regular_repulsion_vs_repulsion_by_degree_/1052522", "title"=>"Regular repulsion vs. repulsion by degree.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-10 03:24:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/1529052"], "description"=>"<p>ForceAtlas2 with gravity at 2 and 5. Gravity brings disconnected components closer to the center (and slightly affects the shape of the components as a side-effect).</p>", "links"=>[], "tags"=>["data visualization", "Infographics", "graphs", "Network Analysis", "social networks", "software engineering", "Software tools", "mathematics", "Applied mathematics", "algorithms", "Sociology", "communications", "semiotics"], "article_id"=>1052524, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Mathieu Jacomy", "Tommaso Venturini", "Sebastien Heymann", "Mathieu Bastian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098679.g003", "stats"=>{"downloads"=>2, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Effects_of_the_gravity_/1052524", "title"=>"Effects of the gravity.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-10 03:24:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/1529053"], "description"=>"<p>ForceAtlas2 with scaling at 1, 2 and 10. The whole graph expands as scaling affects the distance between components as well as their size. Note that the size of the nodes remains the same; scaling is not zooming.</p>", "links"=>[], "tags"=>["data visualization", "Infographics", "graphs", "Network Analysis", "social networks", "software engineering", "Software tools", "mathematics", "Applied mathematics", "algorithms", "Sociology", "communications", "semiotics"], "article_id"=>1052525, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Mathieu Jacomy", "Tommaso Venturini", "Sebastien Heymann", "Mathieu Bastian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098679.g004", "stats"=>{"downloads"=>2, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Effects_of_the_scaling_/1052525", "title"=>"Effects of the scaling.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-10 03:24:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/1529055"], "description"=>"<p>ForceAtlas2 with Edge Weight Influence at 0, 1 and 2 on a graph with weighted edges. It has a strong impact on the shape of the network.</p>", "links"=>[], "tags"=>["data visualization", "Infographics", "graphs", "Network Analysis", "social networks", "software engineering", "Software tools", "mathematics", "Applied mathematics", "algorithms", "Sociology", "communications", "semiotics"], "article_id"=>1052527, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Mathieu Jacomy", "Tommaso Venturini", "Sebastien Heymann", "Mathieu Bastian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098679.g005", "stats"=>{"downloads"=>3, "page_views"=>23, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Effects_of_the_edge_weight_influence_/1052527", "title"=>"Effects of the edge weight influence.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-10 03:24:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/1529056"], "description"=>"<p>ForceAtlas2 without and with the nodes overlapping prevention.</p>", "links"=>[], "tags"=>["data visualization", "Infographics", "graphs", "Network Analysis", "social networks", "software engineering", "Software tools", "mathematics", "Applied mathematics", "algorithms", "Sociology", "communications", "semiotics", "overlapping"], "article_id"=>1052529, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Mathieu Jacomy", "Tommaso Venturini", "Sebastien Heymann", "Mathieu Bastian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098679.g006", "stats"=>{"downloads"=>2, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Effects_of_the_overlapping_prevention_/1052529", "title"=>"Effects of the overlapping prevention.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-10 03:24:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/1529058"], "description"=>"<p>Fruchterman-Rheingold layout at speeds 100, 500 and 2,500 (superposition at two successive steps).</p>", "links"=>[], "tags"=>["data visualization", "Infographics", "graphs", "Network Analysis", "social networks", "software engineering", "Software tools", "mathematics", "Applied mathematics", "algorithms", "Sociology", "communications", "semiotics", "oscillation", "nodes"], "article_id"=>1052531, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Mathieu Jacomy", "Tommaso Venturini", "Sebastien Heymann", "Mathieu Bastian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098679.g007", "stats"=>{"downloads"=>4, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_oscillation_of_nodes_increases_with_speed_/1052531", "title"=>"The oscillation of nodes increases with speed.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-10 03:24:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/1529061"], "description"=>"<p>Evolution of the quality of ForceAtlas2 variants at each iteration (the higher the better). Different values of the local speed give different behaviors. The adaptive local speed achieves the best compromise between performance and quality. The network used is “facebook_ego_0” from our dataset.</p>", "links"=>[], "tags"=>["data visualization", "Infographics", "graphs", "Network Analysis", "social networks", "software engineering", "Software tools", "mathematics", "Applied mathematics", "algorithms", "Sociology", "communications", "semiotics"], "article_id"=>1052533, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Mathieu Jacomy", "Tommaso Venturini", "Sebastien Heymann", "Mathieu Bastian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098679.g008", "stats"=>{"downloads"=>0, "page_views"=>18, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Adaptive_local_speed_is_a_good_compromise_/1052533", "title"=>"Adaptive local speed is a good compromise.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-10 03:24:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/1529064"], "description"=>"<p>Evolution of the quality of ForceAtlas2 variants at each iteration on the other facebook ego-networks of our dataset. The adaptive local speed is always the best. Local speed 0.001 converges poorly because the speed is too low. Local speed 0.1 converges poorly because it oscillates a lot: the speed is too high. Local speed 0.01 is sometimes adapted to the network, and sometimes not, but never outperforms the adaptive speed.</p>", "links"=>[], "tags"=>["data visualization", "Infographics", "graphs", "Network Analysis", "social networks", "software engineering", "Software tools", "mathematics", "Applied mathematics", "algorithms", "Sociology", "communications", "semiotics", "adaptive"], "article_id"=>1052535, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Mathieu Jacomy", "Tommaso Venturini", "Sebastien Heymann", "Mathieu Bastian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098679.g009", "stats"=>{"downloads"=>2, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Effects_of_adaptive_local_speed_on_different_networks_/1052535", "title"=>"Effects of adaptive local speed on different networks.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-10 03:24:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/1529066"], "description"=>"<p>Evolution of the layout quality for a single network over 2048 steps. Rows are the 4 different layouts and columns the 3 different randomizations. The red dot is the “Quick and dirty point” where 50% of the maximum quality is reached, and the blue dot is the “Quasi-optimal point” where 90% of the maximum quality is reached. The full visualization is available at this URL: <a href=\"https://github.com/medialab/benchmarkForceAtlas2/tree/master/benchmarkResults\" target=\"_blank\">https://github.com/medialab/benchmarkForceAtlas2/tree/master/benchmarkResults</a>.</p>", "links"=>[], "tags"=>["data visualization", "Infographics", "graphs", "Network Analysis", "social networks", "software engineering", "Software tools", "mathematics", "Applied mathematics", "algorithms", "Sociology", "communications", "semiotics"], "article_id"=>1052537, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Mathieu Jacomy", "Tommaso Venturini", "Sebastien Heymann", "Mathieu Bastian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098679.g010", "stats"=>{"downloads"=>4, "page_views"=>17, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Records_for_a_single_network_/1052537", "title"=>"Records for a single network.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-10 03:24:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/1529067"], "description"=>"<p>Note that the second and third charts have logarithmic scales. FR is really slow, YH has a good performance and FA2 has a good quality.</p>", "links"=>[], "tags"=>["data visualization", "Infographics", "graphs", "Network Analysis", "social networks", "software engineering", "Software tools", "mathematics", "Applied mathematics", "algorithms", "Sociology", "communications", "semiotics"], "article_id"=>1052538, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Mathieu Jacomy", "Tommaso Venturini", "Sebastien Heymann", "Mathieu Bastian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098679.g011", "stats"=>{"downloads"=>4, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Overall_results_of_the_benchmark_/1052538", "title"=>"Overall results of the benchmark.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-10 03:24:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/1529069"], "description"=>"<p>The lower is the better. Note that both scales are logarithmic. On small networks, FR is the best while FA2_LL is slower. On large networks, FR has a poor performance while other algorithms perform similarly on large networks.</p>", "links"=>[], "tags"=>["data visualization", "Infographics", "graphs", "Network Analysis", "social networks", "software engineering", "Software tools", "mathematics", "Applied mathematics", "algorithms", "Sociology", "communications", "semiotics"], "article_id"=>1052540, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Mathieu Jacomy", "Tommaso Venturini", "Sebastien Heymann", "Mathieu Bastian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098679.g012", "stats"=>{"downloads"=>2, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Quasi_Optimal_Time_over_network_size_/1052540", "title"=>"Quasi-Optimal Time over network size.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-10 03:24:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/1529071"], "description"=>"<p>We find that FA2_LL and FA2 are more readable, because the different areas of the network are more precisely defined. However, we do not know any quality measure that captures this phenomenon.</p>", "links"=>[], "tags"=>["data visualization", "Infographics", "graphs", "Network Analysis", "social networks", "software engineering", "Software tools", "mathematics", "Applied mathematics", "algorithms", "Sociology", "communications", "semiotics", "visibly"], "article_id"=>1052542, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Mathieu Jacomy", "Tommaso Venturini", "Sebastien Heymann", "Mathieu Bastian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098679.g013", "stats"=>{"downloads"=>3, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Layouts_give_visibly_different_results_/1052542", "title"=>"Layouts give visibly different results.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-10 03:24:41"}

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  • {"unique-ip"=>"43", "full-text"=>"45", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"13", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"2"}
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  • {"unique-ip"=>"48", "full-text"=>"53", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"2", "year"=>"2019", "month"=>"5"}
  • {"unique-ip"=>"33", "full-text"=>"29", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"9", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"8"}
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Relative Metric

{"start_date"=>"2014-01-01T00:00:00Z", "end_date"=>"2014-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Computer and information sciences", "average_usage"=>[327, 511]}, {"subject_area"=>"/Computer and information sciences/Network analysis", "average_usage"=>[347, 531]}, {"subject_area"=>"/Social sciences/Sociology", "average_usage"=>[365]}]}
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