MARTINI_enrich_BERTopic_GoodLionNews

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_GoodLionNews")

topic_model.get_topic_info()

Topic overview

Number of topics: 28
Number of training documents: 3150

Click here for an overview of all topics.

Topic ID	Topic Keywords	Topic Frequency	Label
-1	fauci - redpills - full - podcast - pervywood	20	-1_fauci_redpills_full_podcast
0	lies - phildo - sued - followers - idiot	1439	0_lies_phildo_sued_followers
1	netflix - youtube - bitchute - lion - great	302	1_netflix_youtube_bitchute_lion
2	xrp - redpills - netflix - conspiracy - telegram	199	2_xrp_redpills_netflix_conspiracy
3	mariupol - zelensky - russians - kazakhstan - sanctions	142	3_mariupol_zelensky_russians_kazakhstan
4	trumps - biden - ballots - cnn - mccarthy	85	4_trumps_biden_ballots_cnn
5	epstein - tucker - liondisclosure1 - headlines - trafficking	81	5_epstein_tucker_liondisclosure1_headlines
6	ariibrand - detox - autistic - oils - soni	74	6_ariibrand_detox_autistic_oils
7	patriot - discount - episodes - july - mugclub	74	7_patriot_discount_episodes_july
8	redpill - netflix - documentary - uncover - bolshevik	73	8_redpill_netflix_documentary_uncover
9	pill - budweiser - risen - happydays - unapologetically	59	9_pill_budweiser_risen_happydays
10	arrested - prisoners - nicolas - patriots - january	58	10_arrested_prisoners_nicolas_patriots
11	lion - good - streaming - exclusives - audiobooks	50	11_lion_good_streaming_exclusives
12	migrants - assaulted - prostitutes - lybia - belfast	46	12_migrants_assaulted_prostitutes_lybia
13	thetruthseekerschannel - greatest - show - lion - nashville	40	13_thetruthseekerschannel_greatest_show_lion
14	sctransformyourhealth - website - doctor - plandemic - vein	40	14_sctransformyourhealth_website_doctor_plandemic
15	murdered - michael - murdoch - winehouse - naked	39	15_murdered_michael_murdoch_winehouse
16	redpill - netflix - website - links - discover	38	16_redpill_netflix_website_links
17	tartarians - empire - cherokee - mongol - egypt	34	17_tartarians_empire_cherokee_mongol
18	kubrick - moon - nasa - landings - 1969	33	18_kubrick_moon_nasa_landings
19	terrorists - riots - gendarmerie - marseille - belgium	32	19_terrorists_riots_gendarmerie_marseille
20	pedophiles - lgbtq - traffickers - arrested - audrey	32	20_pedophiles_lgbtq_traffickers_arrested
21	zionists - israel - netanyahu - mossad - gaza	31	21_zionists_israel_netanyahu_mossad
22	tartaria - liondisclosure - episodes - vip - discounts	30	22_tartaria_liondisclosure_episodes_vip
23	pervywood - hollywood - creepiest - oprah2 - figureheads	28	23_pervywood_hollywood_creepiest_oprah2
24	trudeau - ontario - trucker - convoys - freedom	26	24_trudeau_ontario_trucker_convoys
25	footballer - panthers - died - collapses - flu	25	25_footballer_panthers_died_collapses
26	vaccine - luciferase - detected - pzifer - syncytial	20	26_vaccine_luciferase_detected_pzifer

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