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D0men1c0/
ISSR_Dark_Web_7Topics

Name: ISSR_Dark_Web_7Topics
Rating: 2.5 (8 reviews)

bertopic

text-classification

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ISSR_Dark_Web_7Topics

This is a BERTopic model. BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable topics from large datasets.

Usage

To use this model, please install BERTopic:

pip install -U bertopic

You can use the model as follows:

python

from bertopic import BERTopic
topic_model = BERTopic.load("D0men1c0/ISSR_Dark_Web_7Topics")

topic_model.get_topic_info()

You can make predictions as follows:

python

sentence = ['closed market']
topic, _ = topic_model.transform(sentence)
topic_model.get_topic_info(topic[0])

Topic overview

Number of topics: 8
Number of training documents: 65529

Click here for an overview of all topics.

Topic ID	Topic Keywords	Topic Frequency	Label
-1	anyone - new - help - free - please	2823	-1_anyone_new_help_free
0	weed - xanax - vendor - cocaine - mg	27613	Drug Vendor Europe
1	market - empire - dream - nightmare - vendor	8645	Dream Vendor Nightmare
2	vendor - scammer - scam - looking - scamming	6236	Trusted Vendor Scams
3	review - vendor review - vendor - review vendor - review review	6907	Vendor MDMA Review
4	mdma - lsd - get - looking - wsm	4230	Drug Discussion
5	order - package - shipping - delivery - pack	6299	Order Shipping & Tracking
6	bitcoin - card - wallet - btc - bank	2776	Financial Services and Products

Training hyperparameters

calculate_probabilities: False
language: None
low_memory: False
min_topic_size: 10
n_gram_range: (1, 2)
nr_topics: None
seed_topic_list: [['tor site', 'drug', 'cocaine', 'ketamine', 'weed', 'trafficking', 'scammer', 'market', 'vendor', 'bitcoin', 'mdma', 'coke', 'lsd', 'heroine', 'xanax', 'tor node', 'tor site', 'gun', 'weapon', 'hacking']]
top_n_words: 10
verbose: True
zeroshot_min_similarity: 0.05
zeroshot_topic_list: [['burglary', 'buy drugs', 'buy weapons', 'child abuse', 'check sale', 'corruption', 'counterfeit money', 'drugs', 'espionage', 'fake IDs', 'find vendor', 'fraud', 'gun', 'hacking', 'kidnapping', 'murder', 'organ trafficking', 'pedophilia', 'rape', 'scammer', 'sell drugs', 'terrorism', 'trafficking']]

Framework versions

Numpy: 1.26.4
HDBSCAN: 0.8.36
UMAP: 0.5.6
Pandas: 2.2.1
Scikit-Learn: 1.4.1.post1
Sentence-transformers: 3.0.1
Transformers: 4.39.3
Numba: 0.60.0
Plotly: 5.22.0
Python: 3.12.2