Twitter Account Analytics

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A few weeks ago, I was thinking about my two Twitter accounts; one personal and one for this site. I was wondering if there was a tool that would allow me to export or web-scrape my Twitter history into .xls or .csv, so I could crank out some pivot tables. There may be multiple ways to do this, but I happened to come across a great resource called Social Bearing (

Social Bearing does exactly what I’d hoped; it allowed me to export my Twitter history into a spreadsheet compatible format (.csv). I believe they are limited to 3,200 Tweets, but my accounts don’t have near that much activity, so I was good to go on @jonamdall and @amdallgallery. Beyond the export, Social Bearing also has a very cool dashboard that’s chocked full of fascinating metrics. Here are my dashboards from the site:

Socialbearing jonamdall Twitter Dashboard

Figure 1. User analytics dashboard for Twitter account @jonamdall.


Socialbearing amdallgallery Twitter Dashboard

Figure 2. User analytics dashboard for Twitter account @amdallgallery.

I love seeing statistics like this, it makes the analyst in me very pumped. I was especially interested in this “sentiment” designation. According to Social Bearing’s FAQ section, sentiment is scored via algorithm from what they call a “bag of words” technique. Basically, each word in a tweet is matched against a set of positive and negative words, then the scores for each word are added up for an overall score in the entire tweet. It’s interesting that I have more good or bad in my personal account, and more neutral in the account for this website. I have a feeling most of those “bad” or “terrible” sentiment tweets were from me blowing of steam during Cowboys games.

For fun, I decided to take my exported data for both accounts and combine them, then see if there was anything interesting to be found. It wasn’t much more interesting than what Social Bearing already provided in the dashboard, but I did get a view of total sentiment for both accounts. It was also interesting to see that I retweet as much as I write regular tweets, and that my retweets are typically either related sports or funny stuff. I’d really like to get a view of total number of likes/favorites per account, but I haven’t been able to find that data on Social Bearing. That may be beyond the scope of what they can pull.

Pivots from Socialbearing data

Figure 3. Pivot tables created from combined exports of @jonamdall and @amdallgallery. Generated by the writer, but based on Social Bearing data.

Very interesting stuff! If you’ve got an itch to analyze your own Twitter account, I’d definitely recommend checking out It’s a powerful tool, is totally free, and doesn’t require you to log in to obtain data. At least, that is the case as of today.


  • Thanks for this link – I think we might try it with our Twitter account at work – it will be interesting to see how our work jargon gets assessed in tweets by sentiment!

    • Sure thing! I think the more activity you have, and interactions from other users (likes, retweets, etc), the more interesting the data is. My accounts don’t have much activity, but I had fun running some more popular users like politicians, celebrities, etc.

      I think for a work Twitter account, it might actually have some real utility beyond just being interesting. You could really get a feel for how the business’s messaging is reaching audiences, which tweets are most effective, etc.

  • Thanks for the tool recommendation. I’m definitely going to give it a try!

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