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

# MARTINI_enrich_BERTopic_GeneralMCNews

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_GeneralMCNews")

topic_model.get_topic_info()
```

## Topic overview

* Number of topics: 38
* Number of training documents: 3780

<details>
  <summary>Click here for an overview of all topics.</summary>
  
  | Topic ID | Topic Keywords | Topic Frequency | Label | 
|----------|----------------|-----------------|-------| 
| -1 | biden - fbi - states - vaccine - ukraine | 20 | -1_biden_fbi_states_vaccine | 
| 0 | ballots - maricopa - rigged - recount - republican | 1715 | 0_ballots_maricopa_rigged_recount | 
| 1 | gaza - netanyahu - jerusalem - airstrikes - terrorists | 198 | 1_gaza_netanyahu_jerusalem_airstrikes | 
| 2 | gunman - victims - active - nypd - nashville | 149 | 2_gunman_victims_active_nypd | 
| 3 | twitter - dorsey - banned - paypal - starlink | 139 | 3_twitter_dorsey_banned_paypal | 
| 4 | pelosi - congressman - mccarthy - republicans - impeachment | 111 | 4_pelosi_congressman_mccarthy_republicans | 
| 5 | vaccines - paxlovid - myocarditis - mrna - transfusion | 101 | 5_vaccines_paxlovid_myocarditis_mrna | 
| 6 | biden - fbi - whistleblowers - bribery - subpoena | 87 | 6_biden_fbi_whistleblowers_bribery | 
| 7 | zelensky - ukrainians - volodymyr - belarus - medvedev | 75 | 7_zelensky_ukrainians_volodymyr_belarus | 
| 8 | blackouts - electricity - shortages - california - surging | 71 | 8_blackouts_electricity_shortages_california | 
| 9 | arrested - trafficking - rapist - indicted - investigators | 69 | 9_arrested_trafficking_rapist_indicted | 
| 10 | bolsonaro - petrobras - paulo - santos - janeiro | 64 | 10_bolsonaro_petrobras_paulo_santos | 
| 11 | doj - subpoenaed - declassified - bannon - dismissed | 63 | 11_doj_subpoenaed_declassified_bannon | 
| 12 | jpmorgan - billionaire - jeffrey - ghislaine - zuckerman | 57 | 12_jpmorgan_billionaire_jeffrey_ghislaine | 
| 13 | misgendered - lgbtq - minors - school - genitals | 55 | 13_misgendered_lgbtq_minors_school | 
| 14 | pandemics - nipah - influenza - h5n1 - poliovirus | 49 | 14_pandemics_nipah_influenza_h5n1 | 
| 15 | kardashian - balenciaga - megyn - skky - milo | 46 | 15_kardashian_balenciaga_megyn_skky | 
| 16 | subliminal - satanists - pentagram - reptilian - symbolism | 46 | 16_subliminal_satanists_pentagram_reptilian | 
| 17 | imran - islamabad - peshawar - faizabad - overthrown | 46 | 17_imran_islamabad_peshawar_faizabad | 
| 18 | fires - explosion - haverstraw - warehouse - massive | 45 | 18_fires_explosion_haverstraw_warehouse | 
| 19 | migrants - border - texas - yuma - smuggling | 45 | 19_migrants_border_texas_yuma | 
| 20 | ufo - norad - airships - spyballoon - surveillance | 44 | 20_ufo_norad_airships_spyballoon | 
| 21 | additives - tyson - chicken - mcdonald - antibiotics | 43 | 21_additives_tyson_chicken_mcdonald | 
| 22 | taiwan - pelosi - spratly - squadrons - pingtan | 40 | 22_taiwan_pelosi_spratly_squadrons | 
| 23 | china - lockdowns - shenzhen - pcr - robotaxi | 37 | 23_china_lockdowns_shenzhen_pcr | 
| 24 | climate - propagandized - experts - robodogs - honeybee | 36 | 24_climate_propagandized_experts_robodogs | 
| 25 | bancorporation - fdic - depositors - plummet - crisis | 35 | 25_bancorporation_fdic_depositors_plummet | 
| 26 | unvaxxed - novavax - mandates - reinstated - plaintiffs | 34 | 26_unvaxxed_novavax_mandates_reinstated | 
| 27 | derailment - hazmat - ohio - dioxin - spills | 32 | 27_derailment_hazmat_ohio_dioxin | 
| 28 | biden - psaki - dictator - deepfaked - granddaughter | 30 | 28_biden_psaki_dictator_deepfaked | 
| 29 | fauci - remdesivir - usaid - rfk - collusion | 29 | 29_fauci_remdesivir_usaid_rfk | 
| 30 | indicted - trump - prosecutorial - manhattan - jurors | 29 | 30_indicted_trump_prosecutorial_manhattan | 
| 31 | brics - rubles - rupee - currencies - yuan | 28 | 31_brics_rubles_rupee_currencies | 
| 32 | zaporizhzhya - donetsk - mykolaiv - nuclear - kryvyi | 28 | 32_zaporizhzhya_donetsk_mykolaiv_nuclear | 
| 33 | aircraft - crashed - landed - turbulence - runway | 22 | 33_aircraft_crashed_landed_turbulence | 
| 34 | jfk - assassinating - snowden - julian - mossad | 21 | 34_jfk_assassinating_snowden_julian | 
| 35 | zuckerberg - meta - instagram - lawsuit - shareholder | 21 | 35_zuckerberg_meta_instagram_lawsuit | 
| 36 | desantis - governor - bush - gitmo - prosecute | 20 | 36_desantis_governor_bush_gitmo |
  
</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
