Error message

  • Notice: Trying to access array offset on value of type int in element_children() (line 6609 of /var/data/sites/methodi.ca-7.63/includes/common.inc).
  • Notice: Trying to access array offset on value of type int in element_children() (line 6609 of /var/data/sites/methodi.ca-7.63/includes/common.inc).
  • Notice: Trying to access array offset on value of type int in element_children() (line 6609 of /var/data/sites/methodi.ca-7.63/includes/common.inc).
  • Notice: Trying to access array offset on value of type int in element_children() (line 6609 of /var/data/sites/methodi.ca-7.63/includes/common.inc).
  • Notice: Trying to access array offset on value of type int in element_children() (line 6609 of /var/data/sites/methodi.ca-7.63/includes/common.inc).
  • Deprecated function: implode(): Passing glue string after array is deprecated. Swap the parameters in drupal_get_feeds() (line 394 of /var/data/sites/methodi.ca-7.63/includes/common.inc).

TATR: Finding Popular Hashtags

Introduction 

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.

Ingredients 
Steps 
  • Open a new Jupyter Notebook and import the following libraries:
    • NLTK
    • PANDAS
    • NUMPY
    • MATPLOTLIB
    • 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
Discussion 

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

Status 
Active
Intermediate
Natural Language Processing
Social Media Analysis
Text Gathering
Visualization
Submitted by Jason on Tue, 05/01/2018 - 16:44