---
tags:
- bertopic
library_name: bertopic
pipeline_tag: text-classification
---

# MARTINI_enrich_BERTopic_RogerHodkinson

This is a [BERTopic](https://github.com/MaartenGr/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_RogerHodkinson")

topic_model.get_topic_info()
```

## Topic overview

* Number of topics: 23
* Number of training documents: 2203

<details>
  <summary>Click here for an overview of all topics.</summary>
  
  | Topic ID | Topic Keywords | Topic Frequency | Label | 
|----------|----------------|-----------------|-------| 
| -1 | pfizer - fauci - vaccinated - lockdowns - published | 20 | -1_pfizer_fauci_vaccinated_lockdowns | 
| 0 | fauci - virologists - conspiracy - laboratories - whistleblower | 1174 | 0_fauci_virologists_conspiracy_laboratories | 
| 1 | pandemics - ghebreyesus - trudeau - sovereignty - iran | 98 | 1_pandemics_ghebreyesus_trudeau_sovereignty | 
| 2 | vaccinated - twindemic - bivalent - booster - updated | 93 | 2_vaccinated_twindemic_bivalent_booster | 
| 3 | vaccinations - unvaccinated - dtap - rotavirus - infant | 78 | 3_vaccinations_unvaccinated_dtap_rotavirus | 
| 4 | masks - washington - vaccination - stanford - exemptions | 66 | 4_masks_washington_vaccination_stanford | 
| 5 | myopericarditis - nuvaxovid - physicians - lymphocytic - fatal | 64 | 5_myopericarditis_nuvaxovid_physicians_lymphocytic | 
| 6 | coroners - cv19 - died - worldwide - 2021 | 61 | 6_coroners_cv19_died_worldwide | 
| 7 | newsom - misinformation - physicians - inoculated - astrazeneca | 59 | 7_newsom_misinformation_physicians_inoculated | 
| 8 | infodemic - reclaimthenet - censored - zuckerberg - agencies | 54 | 8_infodemic_reclaimthenet_censored_zuckerberg | 
| 9 | longcovid - lingering - vax - symptoms - sufferers | 50 | 9_longcovid_lingering_vax_symptoms | 
| 10 | lockdown - china - zhengzhou - sars - wechat | 43 | 10_lockdown_china_zhengzhou_sars | 
| 11 | pregnant - miscarriages - pfizer - placental - multiparous | 42 | 11_pregnant_miscarriages_pfizer_placental | 
| 12 | ivermectin - fda - penicillin - cuomo - miracle | 40 | 12_ivermectin_fda_penicillin_cuomo | 
| 13 | plasmidgate - modrna - polio - snapgene - contaminated | 36 | 13_plasmidgate_modrna_polio_snapgene | 
| 14 | pfizer - whistleblower - paxton - quillivant - lawsuit | 33 | 14_pfizer_whistleblower_paxton_quillivant | 
| 15 | fluoxetine - drugmaker - lilly - shortages - mandrola | 33 | 15_fluoxetine_drugmaker_lilly_shortages | 
| 16 | masks - plastic - waste - expose - diapers | 31 | 16_masks_plastic_waste_expose | 
| 17 | military - mandated - discharged - exemptions - whistleblowers | 30 | 17_military_mandated_discharged_exemptions | 
| 18 | oncologists - brca - leukemias - p53 - lymphocytes | 27 | 18_oncologists_brca_leukemias_p53 | 
| 19 | therealanthonyfauci - rfk - joe - shootings - debaters | 27 | 19_therealanthonyfauci_rfk_joe_shootings | 
| 20 | clots - hypercoagulation - vaccinated - pegylated - embalmed | 23 | 20_clots_hypercoagulation_vaccinated_pegylated | 
| 21 | euthanasia - remdesivir - midazolam - ventilator - murdered | 21 | 21_euthanasia_remdesivir_midazolam_ventilator |
  
</details>

## 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