Introduction
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Definition of Social Network Mapping Web or social network mapping is based on the idea that the connections created on the web between different entities (websites, Twitter accounts, etc.) can be perceived as social links. From a practical perspective, it involves tracing the network created by hyperlinks for websites or the connections between users during a discussion on social networks, represented as a graph. Cartographic analyses highlights the various relationships between accounts or websites, the degree of interaction, frequency, and the significance of each connection. Cartographic analyses brings to light online community territories and allows their dynamics to be observed.
The Visibrain platform offers a unique export format on the market: the GEXF export, the data format for the open-source mapping software Gephi.
By combining the power of Gephi and Visibrain, you can create complete maps of relationships between users with just a few clicks, especially on high-volume topics, as well as content maps by focusing on hashtags.
With Visibrain + Gephi maps, you can identify different communities around a topic and understand the relationships of influence.
With Visibrain, you can create community maps on Twitter, LinkedIn, Instagram, TikTok, Telegram, Threads.
By following the GEXF export buttons you need to go to the User's Tab
Graph example (X data)
Graph example (Instagram Data)
With Visibrain, you can create content maps (hashtags) on Twitter and Instagram.
By following the GEXF export buttons you need to go the Hashtags tab :
Graph example :
Gephi is software designed for real-time visualization, analysis, and exploration of graphs (also known as networks or relational data) of any type. The tool allows you to represent, organize, and arrange structures, shapes, and colors to reveal the hidden properties of a network through visual highlights.
The outputs created can be exported in various formats, including PDF, which allows them to be viewed by a wide audience. Gephi can also export imported data in .csv format.
Formats supported by Gephi: GEXF14, GDF, DOT (language), GraphML, Graph Modeling Language
To produce a network, two pieces of information are required: a list of actors forming the network and a list of relationships between these actors. The actors are referred to as "nodes" and the relationships as "edges" or "arcs." The label corresponds to the name of the node, which is the actor's name.
An arc is directed, meaning the relationship goes from account 1 to account 2. This type of relationship is used, for example, to indicate that account 1 sent a tweet or follows account 2, depending on the data collected.
In the case of Twitter, for example, two types of links can be identified when focusing on a node:
Inbound links: The Twitter account is followed/mentioned by an identified person.
Outbound links: The Twitter account follows/mentions an identified person.
In a graph, a cycle is a simple chain where the endpoints coincide. The same vertex is not encountered twice, except for the one chosen as the starting and ending point.
A graph is referred to as connected if each node in the graph has at least one connecting link to all other points. Two vertices are considered adjacent if they are connected by an edge. A tree is a connected graph that does not contain any cycles.
A graph is considered complete if all pairs of vertices are adjacent.
The interface is structured around three tabs to meet different needs:
An Overview Tab: to analyze the information.
A Data Laboratory: this tab allows you to view your data in the form of a simple table, enabling you to manipulate the information as you would in Excel. A unique feature is the presence of two sub-tabs in the top left corner: a Nodes Tab and a Links Tab. You can switch between data about the actors in your network (e.g., Twitter accounts) and data about the relationships between these actors (e.g., who follows/mentions whom).
The Ranking and Partition Zone: in this area, you can colorize data based on parameters obtained from statistical analysis or separate your data to apply different colors. For instance, you can divide two groups in the diagram and classify them based on various information.
The Spatialization Zone: this tab allows you to select an algorithm to reposition nodes (Twitter or Instagram accounts) optimally and visualize their interactions.
A Filters and Statistics Tab: with this tool, you can remove specific nodes (Twitter accounts) from your network, filter information based on certain parameters, and perform statistical analyses.
The Data Display Tab: this tab allows you to adjust the size of nodes, the links between nodes, and display the names of the nodes.
