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Analysis of Fortune 100 twitter data

Home Page: https://kmcelwee.com/fortune-100-blm-report/site/

Python 2.29% HTML 40.55% JavaScript 2.76% CSS 2.05% Jupyter Notebook 52.34%
blm-dataset fortune-500 corporate-social-responsibility twitter-api blm blm-tweets

fortune-100-blm-report's Introduction

Fortune 100 BLM Report

An analysis of fortune-100-blm-dataset. Link to the website: https://www.kmcelwee.com/fortune-100-blm-report/site/

  • docs: a poorly-named directory for JSON data used in the site
  • figures/tweet-histograms: collection of static tweet histograms useful for debugging
  • fortune-100-blm-dataset: the submodule used to inform analysis.
  • scripts: parsers for generating JSON and querying Twitter.
  • supplementary-data: data brought in from external sources to enrich the BLM dataset.
  • site: where the actual site is hosted.

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fortune-100-blm-report's Issues

Double check every tweet

After finishing data visualization, run a final pass through all tweets to ensure consistency

Wrap report better

Container within the report to hold paragraphs and headers? Otherwise it's just explicitly declaring the width of headers and paragraphs and images

Create legend

This isn't straightforward in D3. Not sure how to best move forward

Spike on publishing options

Isn't combining markdown with charts what Jupyter was made for? But I want a friendlier medium to any reader... so a proper website? I don't want to invest so much time in that! I could generate a website from Markdown which points to the files generated here. The only concern is interactive graphs, but D3 has certainly been used in GitHub pages elsewhere.

Highlight by tag

Create an interface that highlights (with large yellow circle?) the tweets with the selected tags

Spike: How to make tweet histograms larger

We have both the static images and the interactive visualizations. For static images, we can place the legend above the histogram instead of to the right. For dynamic images, see how we can increase circle size, reduce margins, and ensure that the graph is taking up the full given width. Also consider widening default text block width.

Rounding errors found in IDs

Oembed process revealed IDs that had been rounded:

1265004698148495400
1265812305817862100
1266080125805834200

This exists within the dataset in fortune-100-blm-dataset. I believe I manually entered values for Lowe's because of API limits, so that might be what's happening.

  • Request oembed for all tweets ending in 00 to double check that it's limited to these tweets.
  • Dig into fortune-100-blm-dataset repo and double check scripts.
  • Pandas automatically reads the ID column as an integer. Research that this doesn't cause issues.

Improve OEmbed error handling

  • Create a file reviewed-oembed-errors.txt that lists IDs reviewed in #14.
  • Update collect-twitter-oembeds.py to print out errors that are new.
  • Update collect-twitter-oembeds.py to include returned messages with "error" to be included in the "error" field.

Twitter screenshots useful?

Some of the media within tweets could be useful, and it might be a last-ditch way to get twitter-like tooltips.

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