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AIDA-UPM/
MARTINI_enrich_BERTopic_TheTruthAboutCancer_Vaccines

Name: MARTINI_enrich_BERTopic_TheTruthAboutCancer_Vaccines
Availability: InStock

bertopic

text-classification

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MARTINI_enrich_BERTopic_TheTruthAboutCancer_Vaccines

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("AIDA-UPM/MARTINI_enrich_BERTopic_TheTruthAboutCancer_Vaccines")

topic_model.get_topic_info()

Topic overview

Number of topics: 12
Number of training documents: 1350

Click here for an overview of all topics.

Topic ID	Topic Keywords	Topic Frequency	Label
-1	trump - facebook - vaccines - satan - charlene	20	-1_trump_facebook_vaccines_satan
0	vaccine - fauci - deaths - shots - myocarditis	579	0_vaccine_fauci_deaths_shots
1	salvation - jesus - ephesians - nuns - forgive	197	1_salvation_jesus_ephesians_nuns
2	conspiracy - vaccine - eugenics - episode - uncensored	110	2_conspiracy_vaccine_eugenics_episode
3	fbi - trump - antifa - rigged - indictment	95	3_fbi_trump_antifa_rigged
4	thetruthaboutcancer - laetrile - chemotherapy - charlene - episodes	93	4_thetruthaboutcancer_laetrile_chemotherapy_charlene
5	rogerstoneauction - bannon - thestevesanchezshow - faithless - zak	64	5_rogerstoneauction_bannon_thestevesanchezshow_faithless
6	thetruthaboutcancer - disinformation - facebook - vaxx - banned	54	6_thetruthaboutcancer_disinformation_facebook_vaxx
7	retweeting - followers - musk - lol - removed	51	7_retweeting_followers_musk_lol
8	ttac - nashville - jackson - event - trump	34	8_ttac_nashville_jackson_event
9	nowmike - adams - updates - podcast - texas	30	9_nowmike_adams_updates_podcast
10	stonefamilyfund - nydia - cancer - roger - thankyoujesus	23	10_stonefamilyfund_nydia_cancer_roger

Training hyperparameters

calculate_probabilities: True
language: None
low_memory: False
min_topic_size: 10
n_gram_range: (1, 1)
nr_topics: None
seed_topic_list: None
top_n_words: 10
verbose: False
zeroshot_min_similarity: 0.7
zeroshot_topic_list: None

Framework versions

Numpy: 1.26.4
HDBSCAN: 0.8.40
UMAP: 0.5.7
Pandas: 2.2.3
Scikit-Learn: 1.5.2
Sentence-transformers: 3.3.1
Transformers: 4.46.3
Numba: 0.60.0
Plotly: 5.24.1
Python: 3.10.12