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AIDA-UPM/
MARTINI_enrich_BERTopic_childcovidvaccineinjuriesuk

Name: MARTINI_enrich_BERTopic_childcovidvaccineinjuriesuk
Availability: InStock

bertopic

text-classification

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MARTINI_enrich_BERTopic_childcovidvaccineinjuriesuk

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_childcovidvaccineinjuriesuk")

topic_model.get_topic_info()

Topic overview

Number of topics: 23
Number of training documents: 2102

Click here for an overview of all topics.

Topic ID	Topic Keywords	Topic Frequency	Label
-1	vaccinated - astrazeneca - reports - 2022 - mrna	20	-1_vaccinated_astrazeneca_reports_2022
0	lockdown - totalitarianism - cepi - bbc - everyone	1141	0_lockdown_totalitarianism_cepi_bbc
1	myopericarditis - carditis - vaers - tachycardia - inflammation	104	1_myopericarditis_carditis_vaers_tachycardia
2	clots - amyloid - vials - nanoparticles - injected	72	2_clots_amyloid_vials_nanoparticles
3	victims - evidence - ccviuk - officer - warwickshire	67	3_victims_evidence_ccviuk_officer
4	miscarriages - vaers - trimester - caesarean - pfizer	65	4_miscarriages_vaers_trimester_caesarean
5	vaccinated - doctors - schizophrenia - dangerous - roger	64	5_vaccinated_doctors_schizophrenia_dangerous
6	died - soccer - cardiac - sudden - 27	56	6_died_soccer_cardiac_sudden
7	vaers - underreporting - killed - 35 - 2022	54	7_vaers_underreporting_killed_35
8	polio - guillain - encephalopathy - strokes - eudravigilance	54	8_polio_guillain_encephalopathy_strokes
9	vaers - died - reportedlink - 2022 - injected	45	9_vaers_died_reportedlink_2022
10	lockdowns - mask - headteachers - billionaires - abuse	39	10_lockdowns_mask_headteachers_billionaires
11	sars - bioweapon - lies - origins - corbett	39	11_sars_bioweapon_lies_origins
12	mortality - 2022 - millennials - cohort - 40	38	12_mortality_2022_millennials_cohort
13	soldiers - embolisms - unwell - boeing - discharge	33	13_soldiers_embolisms_unwell_boeing
14	novavax - pneumococcal - toddlers - doses - bivalent	29	14_novavax_pneumococcal_toddlers_doses
15	pfizer - pertussis - died - billions - 2009	29	15_pfizer_pertussis_died_billions
16	newsom - minors - kentucky - consent - disallows	29	16_newsom_minors_kentucky_consent
17	gardasil - died - 17 - injection - boy	28	17_gardasil_died_17_injection
18	injuries - mhra - booster - reports - 229	27	18_injuries_mhra_booster_reports
19	unvaxed - deadlier - england - 495 - quadruple	25	19_unvaxed_deadlier_england_495
20	metastasizing - brca - toxshot - interferon - micrornas	24	20_metastasizing_brca_toxshot_interferon
21	hpv - bibfertility - ovaries - postmenopausal - antibodies	20	21_hpv_bibfertility_ovaries_postmenopausal

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