TATR: Finding Popular Hashtags


This recipe is part of the Text Analysis for Twitter Research (TATR) series. In this recipe we will show you how to use a dataset of Tweets to find the most popular hashtags by date. The results can then be manipulated by placing them in a Panda dataframe and visualized by plotting the most popular hashtag points over time.

  • Open a new Jupyter Notebook and import the following libraries:
    • NLTK
    • PANDAS
    • NUMPY
    • AST
  • Import Twitter data
  • Collapse each date’s hashtags into a list
  • Write a helper function to determine most popular hashtag for each date
  • Use the Pandas apply and lambda feature to save the most popular hashtags into columns and display as a graph
  • Save the Pandas dataframe data of the most popular hashtags as a CSV
  • Apply a graphing function to visualize the results

The TATR library was presented as an academic poster in 2018’s Congress held in Regina, SK. For a PDF version of the full poster, please visit:

Next steps / further information 

Certain aspects of this recipe draw upon code from the companion TATR notebooks and recipes. In particular, please see:

TATR: Panda and CSV of Tweets

TATR: Graphing Twitter Data