MARTINI_enrich_BERTopic_mindcontrolmonarchmkultra

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:

from bertopic import BERTopic
topic_model = BERTopic.load("AIDA-UPM/MARTINI_enrich_BERTopic_mindcontrolmonarchmkultra")

topic_model.get_topic_info()

Topic overview

• Number of topics: 13
• Number of training documents: 1552

Click here for an overview of all topics.

Topic ID	Topic Keywords	Topic Frequency	Label
-1	illuminati - morrison - satanic - torture - monarch	25	-1_illuminati_morrison_satanic_torture
0	illuminati - freemasons - lucifer - satanic - pope	963	0_illuminati_freemasons_lucifer_satanic
1	blogs - archived - deyoutubeised - censorship - tiktoker	139	1_blogs_archived_deyoutubeised_censorship
2	pizzagate - epstein - podesta - cathyfoxblog - clinton	60	2_pizzagate_epstein_podesta_cathyfoxblog
3	balenciaga - kardashian - britney - bondage - conservatorship	54	3_balenciaga_kardashian_britney_bondage
4	mkultra - laura - survivor - podcast - demons	49	4_mkultra_laura_survivor_podcast
5	satanists - ritual - allah - allegations - polanski	47	5_satanists_ritual_allah_allegations
6	mariupol - ukrainehumanrightsabuses - satanists - svyatogorsk - ultranationalist	47	6_mariupol_ukrainehumanrightsabuses_satanists_svyatogorsk
7	sextortion - mormon - ghislaine - linked - cathyfoxblog	41	7_sextortion_mormon_ghislaine_linked
8	bitchute - survivors - podcast - rachelle - judith	39	8_bitchute_survivors_podcast_rachelle
9	mindcontrol - nsa - links - satteliyte - electromagnetic	32	9_mindcontrol_nsa_links_satteliyte
10	ukrainehumanrightsabuses - органов - украинские - transplants - slavyangrad	28	10_ukrainehumanrightsabuses_органов_украинские_transplants
11	totaldisclosure - jonbenet - leather - hanging - episodes	28	11_totaldisclosure_jonbenet_leather_hanging

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