BERTopic_hurricane_tweet
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("cindyangelira/BERTopic_hurricane_tweet")
topic_model.get_topic_info()
Topic overview
- Number of topics: 11
- Number of training documents: 811
Click here for an overview of all topics.
| Topic ID | Topic Keywords | Topic Frequency | Label |
|---|---|---|---|
| -1 | medicare - theft - medical - harvey - identity | 1 | -1_medicare_theft_medical_harvey |
| 0 | gofundme - donate - houstonstrong - texas - houston | 111 | Weather Updates |
| 1 | plaza - txmedcenter - medical - instagram - here | 516 | Relief Efforts |
| 2 | hurricaneharvey - houston - harvey - hurricane - houstonflood | 74 | Rescue Operations |
| 3 | harvey - hurricane - flooded - houston - tx | 33 | Flooding Reports |
| 4 | houston - astros - harvey - snow - houstonstrong | 28 | Storm Damage Reports |
| 5 | harvey - reliefforharvey - hurricaneharvey - relief - houstonians | 23 | 5_harvey_reliefforharvey_hurricaneharvey_relief |
| 6 | rescued - hurricaneharvey - - - | 14 | 6_rescued_hurricaneharvey__ |
| 7 | hurricaneharvey - hurricane - - - | 4 | 7_hurricaneharvey_hurricane__ |
| 8 | harvey - flooding - houston - floodwaters - flood | 4 | 8_harvey_flooding_houston_floodwaters |
| 9 | houston - hurricaneseason - hurricaneharvey - harvey - weather | 3 | 9_houston_hurricaneseason_hurricaneharvey_harvey |
Training hyperparameters
- calculate_probabilities: False
- language: None
- low_memory: False
- min_topic_size: 15
- n_gram_range: (1, 1)
- nr_topics: None
- seed_topic_list: None
- top_n_words: 10
- verbose: False
- zeroshot_min_similarity: 0.85
- zeroshot_topic_list: ['Weather Updates', 'Evacuation Information', 'Emergency Services', 'Relief Efforts', 'Rescue Operations', 'Flooding Reports', 'Traffic and Road Closures', 'Government and Local Authority Announcements', 'Personal Stories and Experiences', 'Storm Damage Reports', 'Others']
Framework versions
- Numpy: 1.26.4
- HDBSCAN: 0.8.38.post1
- UMAP: 0.5.6
- Pandas: 2.2.2
- Scikit-Learn: 1.2.2
- Sentence-transformers: 3.1.0
- Transformers: 4.44.0
- Numba: 0.60.0
- Plotly: 5.22.0
- Python: 3.10.14
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