Top keywords (global influence):
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@rhumbl allows to visualize any #excel or #csv spreadsheet as a network graph https://rhumbl.com/

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@vis allows to create networks but its functionality is based more on #mind_maps it takes #excel data as input https://vis.occrp.org

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#connect_the_dots is a project by @databasic which can visualize any #csv or #excel data as a network and export as #gefx or #png

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@wtfcsv can be used to visualize #csv and #excel as a #tag_cloud

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@kumu is a tool that can be used to create network #maps of #concepts and to showcase their relationships along with a complimentary #text https://kumu.io

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@infranodus can be used to visualize #text, #csv, #excel and can export data in #csv and #gexf format

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#kumu basically creates #mind_maps

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@linkurious can visualize #neo4j data and can also be used to create maps https://linkurio.us

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#infranodus works on #neo4j

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#linkurious is like a more technical version of #kumu and has more features: it allows to perform the basic #network_analysis calculations

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@infranodus performs #network_analysis on the data to detect the most important relationships, hubs, and #structural properties of the relations

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@graph_commons can visualize #concepts and be used to #mind_maps. It also provides basic #structural information and rudimentary #network_analysis https://graphcommons.com

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@mindnode can be used to create #mind_maps https://mindnode.com

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@keylines can be used to perform #network_analysis and better understand the #structural properties of a system of relationships https://cambridge-intelligence.com/keylines

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@greaterthanthesum makes software that can be used to create #maps and networks of #concepts

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@fluorish can be used to visualize #concepts from #csv and #excel and their relations and the basic #network_analysis https://flourish.studio

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@graphonline helps create graphs and provides basic #network_analysis features (eg shortest path) https://graphonline.ru

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@graphistry can visualize network data from #neo4j or #csv sources and can be used for #storytelling https://www.graphistry.com/

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#kumu can be used for #storytelling

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@yworks is a graph visualization suite that can be used to build graphs and to get interesting insights about the #structural properties (it takes #csv and #excel data as import)

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@polinode offers organizational network analysis SaaS and can perform #network_analysis and get insights about the #structural properties of a network https://www.polinode.com/

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@quid is a platform to get insights in data using #network_analysis http://quid.com

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@Arcade_Analytics can do #network_analysis and is best suited for #storytelling

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#graph_commons is best suited for #storytelling using the graphs

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@cytoscape performs #network_analysis and #network_visualization

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#infranodus is a #network_visualization tool

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#arcade_analytics can visualise #neo4j data

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@gephi is one of the best #network_analysis and #network_visualization tools

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#networkrepository is a tool for #network_visualization mainly used in science

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#infranodus can visualise a network of #concepts

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#infranodus can be used to create #mind_maps

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@lynksoft can be used to build #mind_maps and #network_visualization and perform #network_analysis on the connected data

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@nodexl is an #excel tool for #network_analysis

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@rhumbl can be used to map #concepts and #mind_maps

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@rawgraphs #mind_maps #network_visualization https://rawgraphs.io/

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    The topics are the nodes (words) that tend to co-occur together in the same context (next to each other).

    We use a combination of clustering and graph community detection algorithm (Blondel et al based on Louvain) to identify the groups of nodes are more densely connected together than with the rest of the network. They are aligned closer to each other on the graph and are given a distinct color.
    Most Influential Elements:
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    We use the Jenks elbow cutoff algorithm to select the top prominent nodes that have significantly higher influence than the rest.

    Click the Reveal Non-obvious button to remove the most influential words (or the ones you select) from the graph, to see what terms are hiding behind them.

    The most influential nodes are either the ones with the highest betweenness centrality — appearing most often on the shortest path between any two randomly chosen nodes (i.e. linking the different distinct communities) — or the ones with the highest degree.

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    Structural Gap
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    A structural gap shows the two distinct communities (clusters of words) in this graph that are important, but not yet connected. That's where the new potential and innovative ideas may reside.

    This measure is based on a combination of the graph's connectivity and community structure, selecting the groups of nodes that would either make the graph more connected if it's too dispersed or that would help maintain diversity if it's too connected.

    Latent Topical Brokers
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    These are the latent brokers between the topics: the nodes that have an unusually high rate of influence (betweenness centrality) to their freqency — meaning they may appear not as often as the most influential nodes but they are important narrative shifting points.

    These are usually brokers between different clusters / communities of nodes, playing not easily noticed and yet important role in this network, like the "grey cardinals" of sorts.

    Emerging Topics
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    Top Relations
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    ⤓ Download   ⤓ Directed Bigrams   ?

    The most prominent relations between the nodes that exist in this graph are shown above. We treat the graph as undirected by default as it allows us to better detect general patterns.

    As an option, you can also downloaded directed bigrams above, in case the direction of the relations is important (for any application other than language).

     
    Main Topics
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    Most Influential Words
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