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In this project, we implemented a topic detection system on Twitter. This system reads tweets from a data stream and assigns them to one of the existing clusters or a new one. Each cluster acts as an agent, which makes the proposed approach a multi-agent system. There is also a coordinator, who monitors the whole system and coordinates the agent.

License: MIT License

Python 82.00% Jupyter Notebook 18.00%
nlp topic-detection multi-agent data-stream elixir clustering-algorithm labse

comstream's Introduction

ComStream


Introduction:

In this project, we implemented a topic detection system on Twitter. This system reads tweets from a data stream, and assigns them to one of the existing clusters or a new one. Each cluster acts as an agent, which makes the proposed approach a multi-agent system. There is also a coordinator, who monitors the whole system and coordinates the agent.The proposed approach has been experimented on two datasets: The COVID-19 and the FA CUP. This project has been explained with greater detail in a paper, publicly available in ComStreamClust .

System Overview

logo

How to use the code ? ๐Ÿค—

Data file must be a pandas DataFrame in pickle format having these columns :

  • text
  • created_at
  • status_id

For example : example

warning: Data must be sorted based on created_at in ascending order

Requirements

  • pandas
  • colorama

Contributers:

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