/Twitter-Trending-NER-Sentiment-Analysis

Mine Tweets from twitter & perform NLP analysis

Primary LanguageJupyter Notebook

Twitter-Trending-NER-Sentiment-Analysis

Mining Tweets from twitter & perform NLP analysis & Pulse check

preview This is a quick and dirty way to get a sense of what's trending on Twitter related to a particular Topic. For my use case, I am focusing on the city of Seattle but you can easily apply this to any topic.

This Notebook:

  • Scrapes Tweets related to the Topic mentioned.
  • Extracts relevant Tags from the text (NER: Named Entity Recognition).
  • Does Sentiment Analysis on those Tweets.
  • Provides some visualizations in an interactive format to get a 'pulse' of what's happening.

Tweepy - scrape Twitter data.

Flair - NER / Sentiment Analysis.

Seaborn - visualizations.

The Twitter scrape code here was taken from: https://bhaskarvk.github.io/2015/01/how-to-use-twitters-search-rest-api-most-effectively. My thanks to the author.

We need to provide a Search term and a Max Tweet count. Twitter lets you to request 45,000 tweets every 15 minutes so setting something below that works.