Slightly more advanced graphs

How to visualise Twitter data in 5 minutes

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Today I’ll show how you can visualise Twitter data (for example for a local SEO conference as I did in this example) to generate nice curated content and display trends. Hopefully you’ll find this as useful as I did.

Here’s a taster of how the graphs you create today may look:

Slightly more advanced graphs

Slightly more advanced graphs



Minutes 1-2

Go to https://scraperwiki.com/ and set yourself up with a free account. Then do the same on https://datahero.com/.

ScraperWiki we’ll use for scraping twitter data and data hero for displaying it nicely.

Minutes 3-4

Go to your new ScraperWiki account:

  1. Click on ‘Create a new dataset’
  2. ‘Search for new followers’
  3. Refer to this list when creating your query for the next screen, mine was: #brightonseo since:2013-09-12 until:2013-09-14
  4. Then the app will ask you to authorise it via your Twitter account
  5. Then press on ‘View as a table’
  6. Then ‘Download as a spreadsheet’ and download ‘all_tables.xls’
  7. Review the data to ensure it looks natural – ie. a big event attracts hundreds of tweets or thousands, so if you only have 50 there’s something wrong. You may have to re-run the scraper using different settings. Also remove irrelevant days (by deleting rows) if you only want data for a given day.

Minutes 4-5

Go to your DataHero account, login and click on ‘Upload’ next to ‘your data’.

  1. Choose the .csv export from ScraperWiki
  2. You will be suggested charts based on it, I prefer to choose ‘Create New Chart’
  3. Then drag and drop data you’d like to visualise to the space on the right.
  4. This is the kind of a screen you should be seeing after dropping in two or even one bit of data, it really depends what you’d like to visualise, for a start I suggest just using ‘created at’ column to see at what times there were the most tweets:

    Basic Chart from DataHero

    Basic Chart from DataHero

  5. Once you’re done with a particular graph press on Export and voila you have your graphical representation of Twitter data.

 

That’s it – now you have your first basic graph. I encourage you to experiment with different bits of data and graphs and colours.

The data for me wasn’t 100% accurate, but it was enough to show the trends etc. Here’s the end effect of a few graphs that took me about 30 minutes or so

For full versions of the graphs I generated see the original at our Jellyfish blog.

I really hope you enjoyed this post and will give it a try. Please let me know if you figure out better ways to use the data or find any mistakes in what I’ve done – I only learned this today.

This is heavily based on this post, which I read thanks to Gisele today (Thanks again Gisele!)

 

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How to visualise Twitter data in 5 minutes by

Hey, I'm Krystian - an SEO-holic living and working in Brighton.

4 thoughts on “How to visualise Twitter data in 5 minutes

  1. This is pretty cool dude, this might come in handy for some of the other major SEO conferences around the UK as well?

    I guess it might also be useful for brands looking to monitor a Hash Tag Campaign?

    Good work

    • Oh ye good point, I didn’t think about Hash Tag Campaign monitoring – during the day and post event to see where the spikes happen! Thanks for that suggestion.

    • Thanks for the comment mate, yeah I’m thinking of covering an event this way.

      A full week may be too much data for this tool, but I’ll give it a shot! May lead to another post as I may need a bigger scraper/data tool.

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