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https://github.com/bellingcat/gesara-entity-viz.git
synced 2026-06-13 05:58:33 +03:00
changed bbox of network, added variable in json data to set label threshold, changed to British spelling convention
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@@ -14,18 +14,17 @@ const DescriptionPanel: FC = () => {
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}
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>
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<p>
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This visualisation represents a <i>network</i> of{" "}
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This interactive visualisation represents a <i>network</i> of{" "}
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<a target="_blank" rel="noreferrer" href="https://spacy.io/usage/linguistic-features#named-entities">
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named entities
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</a> in English-language posts archived in a database of Telegram channels that have posted about the GESARA conspiracy theory. Each{" "}
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<i>node</i> represents an entity, <i>edges</i> between nodes indicate that one or more posts contain both entities
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.
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<i>node</i> represents an entity, <i>edges</i> between nodes indicate that one or more posts contain both entities.
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</p>
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<p>
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This kind of visualization shows the ecosystem of the people, organizations, and ideas these conspiracy Telegram channels talk about, as well as the connections between them.
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This kind of visualisation shows the ecosystem of the people, organisations, and ideas these conspiracy Telegram channels talk about, as well as the connections between them.
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</p>
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<p>
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Some social media channels were identified by researchers from{" "}
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Some Telegram channels were identified by researchers from{" "}
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<a target="_blank" rel="noreferrer" href="https://www.bellingcat.com/">
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Bellingcat
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</a>{" "}and{" "}
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@@ -59,14 +58,13 @@ const DescriptionPanel: FC = () => {
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.
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</p>
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<p>
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The network was visualized using{" "}
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The network was visualised using{" "}
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<a target="_blank" rel="noreferrer" href="https://gephi.org/">
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Gephi
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</a>. Node sizes are related to the number of channels the entity was posted about in the database.
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Nodes are colored based a{" "}
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</a>. The radius of each node is proportional to the number of channels in the database whose posts mention the entity. Nodes are coloured based on a{" "}
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<a target="_blank" rel="noreferrer" href="https://arxiv.org/abs/0803.0476">
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community detection algorithm
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</a>.
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</a>. Edges are weighted by the number of posts that mention both entities.
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For visualisation purposes, edges were pruned using the{" "}
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<a target="_blank" rel="noreferrer" href="https://github.com/naviddianati/GraphPruning">
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Marginal Likelihood Filter
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@@ -53,7 +53,7 @@ const Root: FC = () => {
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defaultNodeType: "image",
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labelDensity: 0.07,
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labelGridCellSize: 60,
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labelRenderedSizeThreshold: 10,
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labelRenderedSizeThreshold: dataset.labelThreshold,
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labelFont: "Lato, sans-serif",
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zIndex: true,
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}}
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