smacawi/bert-topics

Bridging the gap between supervised classification and unsupervised topic modelling for social-media assisted crisis management (Adapt-NLP EACL 2021)

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Emerging

When a crisis hits, this helps emergency response teams quickly understand the main topics emerging from social media messages. It takes in a stream of social media text, like tweets during a snowstorm, and identifies key themes and categories. This is for crisis managers, social media analysts in public service, or emergency responders who need to make sense of large volumes of real-time public sentiment.

No commits in the last 6 months.

Use this if you need to rapidly categorize and understand the dominant subjects within social media data during an unfolding crisis or event.

Not ideal if you're looking for a general-purpose topic modeling tool for everyday text analysis that isn't focused on crisis management.

crisis-management emergency-response social-media-monitoring public-safety disaster-preparedness
Stale 6m No Package No Dependents
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Maturity 16 / 25
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Language

Jupyter Notebook

License

MIT

Last pushed

Apr 20, 2021

Commits (30d)

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