MARTINI_enrich_BERTopic_whitelaborstrikeww
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_whitelaborstrikeww")
topic_model.get_topic_info()
Topic overview
- Number of topics: 13
- Number of training documents: 1445
Click here for an overview of all topics.
| Topic ID | Topic Keywords | Topic Frequency | Label |
|---|---|---|---|
| -1 | whites - diversity - capitalist - judeo - biden | 21 | -1_whites_diversity_capitalist_judeo |
| 0 | immigrants - unions - h1b - whites - borders | 825 | 0_immigrants_unions_h1b_whites |
| 1 | antifa - riots - arrested - prosecutors - gunman | 189 | 1_antifa_riots_arrested_prosecutors |
| 2 | zionists - israelis - gaza - semitism - goyim | 76 | 2_zionists_israelis_gaza_semitism |
| 3 | strikes - biden - railway - salaried - justicereport | 70 | 3_strikes_biden_railway_salaried |
| 4 | massacre - negro - 1919 - strikebreakers - thibodaux | 46 | 4_massacre_negro_1919_strikebreakers |
| 5 | blackrock - golman - feinstein - jews - executive | 43 | 5_blackrock_golman_feinstein_jews |
| 6 | discriminated - lawsuit - undersheriff - cincinnati - fired | 35 | 6_discriminated_lawsuit_undersheriff_cincinnati |
| 7 | whiteness - racists - trannyism - radicalize - saviorism | 34 | 7_whiteness_racists_trannyism_radicalize |
| 8 | black - discrimination - hispanic - deaths - researchers | 30 | 8_black_discrimination_hispanic_deaths |
| 9 | apartheid - afrikaner - ramaphosa - potchefstroom - nedbank | 28 | 9_apartheid_afrikaner_ramaphosa_potchefstroom |
| 10 | mussolini - fascists - marxism - blackshirt - bolshevik | 26 | 10_mussolini_fascists_marxism_blackshirt |
| 11 | riots - chinatown - 1907 - miners - australian | 22 | 11_riots_chinatown_1907_miners |
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
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