From 9f39ceee7b7178958981c5d147ce9209237b3b43 Mon Sep 17 00:00:00 2001 From: Tristan Lee Date: Fri, 16 Dec 2022 01:13:35 -0600 Subject: [PATCH] changed bbox of network, added variable in json data to set label threshold, changed to British spelling convention --- README.md | 14 +++++++------- public/dataset_entities.json | 2 +- ...isualization.py => generate_visualisation.py} | 7 +++++-- src/types.ts | 3 ++- src/views/DescriptionPanel.tsx | 16 +++++++--------- src/views/Root.tsx | 2 +- 6 files changed, 23 insertions(+), 21 deletions(-) rename scripts/{generate_visualization.py => generate_visualisation.py} (96%) diff --git a/README.md b/README.md index b92ce4c..204a6b2 100644 --- a/README.md +++ b/README.md @@ -1,22 +1,22 @@ -# GESARA Named Entity Network Visualization +# GESARA Named Entity Network Visualisation -This project generates an [interactive visualization](https://bellingcat.github.io/gesara-entity-viz/) of [named entities](https://spacy.io/usage/linguistic-features#named-entities) in English-language posts archived in a database of Telegram channels that have posted about the GESARA conspiracy theory. +This project generates an [interactive visualisation](https://bellingcat.github.io/gesara-entity-viz/) of [named entities](https://spacy.io/usage/linguistic-features#named-entities) in English-language posts archived in a database of Telegram channels that have posted about the GESARA conspiracy theory. -This visualization was developed by Bellingcat based on an excellent [Sigma.js demo](https://github.com/jacomyal/sigma.js/tree/main/demo), and uses [react-sigma-v2](https://github.com/sim51/react-sigma-v2) to interface sigma.js with React. +This visualisation was developed by Bellingcat based on an excellent [Sigma.js demo](https://github.com/jacomyal/sigma.js/tree/main/demo), and uses [react-sigma-v2](https://github.com/sim51/react-sigma-v2) to interface sigma.js with React. -You can view the live visualization [here](https://bellingcat.github.io/gesara-entity-viz/). With GitHub pages configured, after making changes to the `main` branch, you need th run the command `npm run deploy` for the latest changes to be reflected in the live visualization. +You can view the live visualisation [here](https://bellingcat.github.io/gesara-entity-viz/). With GitHub pages configured, after making changes to the `main` branch, you need to run the command `npm run deploy` for the latest changes to be reflected in the live visualisation. ## Python Scripts -In the `scripts/` subdirectory, you can run Python scripts that were used to generate the network and visualization: +In the `scripts/` subdirectory, you can run Python scripts that were used to generate the network and visualisation: ### `generate_network.py` Extracts the data from a PostgreSQL database, cleans the entity data, generates a NetworkX graph, prunes the edges using the [Marginal Likelihood Filter](https://github.com/naviddianati/GraphPruning), and exports the pruned graph. -### `generate_visualization.py` +### `generate_visualisation.py` -After visualizing the network using [Gephi](https://gephi.org/) (using the Force Atlas 2 algorithm, with the "LinLog mode" and "Prevent Overlap" options enabled, and exporting as the file `entity_network_layout.graphml`), this script converts the node, edge, and cluster data into a format readable by this sigma.js project. +After visualising the network using [Gephi](https://gephi.org/) (using the Force Atlas 2 algorithm, with the "LinLog mode" and "Prevent Overlap" options enabled, and exporting as the file `entity_network_layout.graphml`), this script converts the node, edge, and cluster data into a format readable by this sigma.js project. ## NPM Scripts diff --git a/public/dataset_entities.json b/public/dataset_entities.json index cfabf78..3138edf 100644 --- a/public/dataset_entities.json +++ b/public/dataset_entities.json @@ -1 +1 @@ -{"nodes":[{"x":-44.58211,"y":-676.76794,"label":"a&e","size":1.02248132,"frequency":360,"cluster":"8","key":"a&e"},{"x":249.34668,"y":-293.99762,"label":"hefner","size":0.84642786,"frequency":298,"cluster":"8","key":"hefner"},{"x":231.47716,"y":-286.1582,"label":"hugh hefner","size":1.9936152,"frequency":702,"cluster":"8","key":"hugh 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- This visualisation represents a network of{" "} + This interactive visualisation represents a network of{" "} named entities in English-language posts archived in a database of Telegram channels that have posted about the GESARA conspiracy theory. Each{" "} - node represents an entity, edges between nodes indicate that one or more posts contain both entities - . + node represents an entity, edges between nodes indicate that one or more posts contain both entities.

- 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. + 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.

- Some social media channels were identified by researchers from{" "} + Some Telegram channels were identified by researchers from{" "} Bellingcat {" "}and{" "} @@ -59,14 +58,13 @@ const DescriptionPanel: FC = () => { .

- The network was visualized using{" "} + The network was visualised using{" "} Gephi - . Node sizes are related to the number of channels the entity was posted about in the database. - Nodes are colored based 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{" "} community detection algorithm - . + . Edges are weighted by the number of posts that mention both entities. For visualisation purposes, edges were pruned using the{" "} Marginal Likelihood Filter diff --git a/src/views/Root.tsx b/src/views/Root.tsx index 34f93f7..1714fdf 100644 --- a/src/views/Root.tsx +++ b/src/views/Root.tsx @@ -53,7 +53,7 @@ const Root: FC = () => { defaultNodeType: "image", labelDensity: 0.07, labelGridCellSize: 60, - labelRenderedSizeThreshold: 10, + labelRenderedSizeThreshold: dataset.labelThreshold, labelFont: "Lato, sans-serif", zIndex: true, }}