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Naive Bayes model is trained to detect whether a tweet signifies a problem faced by a citizen or not. The problems are analyzed to get information about any event, citizens’ complaints, or requests, and stored in the database along with the location in real-time.

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R-A-N-N/Final-Year-Project

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Final-Year-Project

Detecting Citizen Problems and Their Locations Using Twitter Data

  • This Project focuses on the ways of finding citizen problems with their locations by using tweet data.
  • Analyzing the collected data to get information of any city event, citizen's complaint or requests about a problem.
  • Detecting tweets, which have any city problem
  • Two datasets were created consists of the tweets that have an event information or a problem the tweets, which have other information not related to our study.
  • Then Naive Bayes classifier was trained on the annotated tweets and was tested on a separate set of tweets.
  • A location recognizer, which finds the Turkish place names in a text, is created and applied on the tweets that are marked as information-containing by the classifier to detect the location of the problem precisely.

Domain

  • ML
  • Data Analysis
  • Web Development

IEEE Research Paper : Link

Google Docs : Link

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Naive Bayes model is trained to detect whether a tweet signifies a problem faced by a citizen or not. The problems are analyzed to get information about any event, citizens’ complaints, or requests, and stored in the database along with the location in real-time.

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