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# AlertEmbeddings
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Abuse detection in online conversations with text and graph embeddings
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AlertEmbeddings
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*Abuse detection in online conversations with text and graph embeddings*
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## Datasets
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# Description
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This set of scripts aims at learning various text ang graph embeddings from online conversations to detect online abuse.
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Datasets are available at https://zenodo.org/records/11617245
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# Data
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The datasets are available at https://zenodo.org/records/11617245.
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To use the SpaceOrigin dataset, unzip the `SpaceOrigin_graphs.zip` archive into the `in/graphs` folder.
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## Running tests
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conversation should be added in the `in/text_conversations` folder as a separate file for each conversation with each line corresponding to a message. An example is available.
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### Signed Graph2vec
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```
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python src/signed_graph2vec.py --input-path "dataset/*.graphml" --output-path output/embeddings.csv
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```
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# Organization
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Here are the folders composing the project:
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* Folder `in`: input data, including the textual conversations and graphs.
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* Folder `SGCN`: set of scripts to learn embeddings using the SGCN method.
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* Folder `signed_graph2vec`: set of scripts to learn embeddings using the SG2V method.
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* `text_embeddings.py`: script to learn the text embeddings.
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* `unsigned_graph_embeddings.py`: script to apply te standard unsigned graph embedding models.
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### SGCN
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Based on https://github.com/benedekrozemberczki/SGCN
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```
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python SGCN/main.py --layers 96 32 --learning-rate 0.01 --reduction-dimensions 64 --epochs 10 --reduction-iterations 10 --edge-path dataset/edges.csv --embedding-path output/embedding.csv --regression-weights-path output/weights.csv
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```
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# Installation
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This library requires python 3.8+
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Dependencies car be installed with ``` pip install -r requirements.txt ```

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