Tag Archives: Twitter
We are happy to welcome this guest post on a community tool by Bastian Greshake Tzovaras. Bastian is the director of research at the Open Humans project. He can be found online at @gedankenstuecke. -Steven
I’ve built a Twitter analysis web application that’s open to everyone to use and learn from. Often the best data for learning something about yourself are data you’ve already collected; sometimes without even being explicitly aware of collecting it. Social media activity, for example. We often send off Facebook posts or tweets with very little thought about the metadata that we generate in doing so. Where was I when I made that post? What time was it? What type of content did it contain? Did I retweet or reply to another person’s post? And, of course, what did my post contain?
This data can be extremely powerful – for others. The language you use in your Tweets can be used to predict your age as well as your income. Twitter uses the data to gather information about your likes, dislikes, and possessions – among other topics. But what if you want to learn about yourself with your own Twitter data?
The tool I created allows anybody to explore their own Twitter archive in detail. First, you’ll want to request your archive from Twitter. It will contain all the tweets you have ever sent, with not only the text but all the metadata as well. To look at these metadata, go to my small web application called TwArχiv (pronounced tw-archive), which allows you to upload your data and explore it using interactive graphs.
For instance, you can see how the nature of the tweets you send change over time. Are you replying more to people than you used to or is it all just retweets by now? For my own data it seems that finishing up my PhD work had quite an impact, starting in late 2016. With less procrastination I wrote fewer unprompted tweets. Instead, replying to people became more central to my Twitter experience.
There is also plenty of research on gender bias in social media usage and whose voices are being amplified, with men being overwhelmingly favored. TwArχiv allows one to do some soul searching on this. It tries to predict the gender of the people you interact with based on their first names and shows you whether your reply and retweet behaviour is gender-balanced.
My own graphs show that I had (and have) a good way to go here. Especially 2010 is wildly off when it comes to the gender representation in my Twitter interactions. What happened during that time? I was politically active in the German Pirate Party, which was infamous for being a “boys club”.
If you have geolocation enabled on your tweets, you can get an idea of where you tweet. With a fully zoomable map, TwArχiv allows you to explore the globe on all scales to see the broader picture as well as street-level tweet distributions. As a first attempt of seeing movement patterns, you can also get a time-stamped version of the map that highlights locations one tweet at a time.
If you want to give a try with your own archive, you can head to TwArχiv.org. The data storage is handled by Open Humans and by default your archive and the resulting visualizations will be private. (You can choose to make them public, though, to share them with your friends and followers – mine are here!).
A note: The Twitter archive does not contain any direct messages but only your tweets, so if you have a public Twitter account the archive is basically all your “public Twitter interactions”.
If you have ideas on how to extend the functionality of TwArχiv or you want to code your own Twitter archive analysis, you could even get funding to do so: The Open Humans’ mini-grants of USD 5,000 for projects that will enrich the Open Humans ecosystem are a perfect fit for this kind of data visualization and analysis.
It’s no secret we love data here at Quantified Self, but we also love seeing how people interact with data. We’ve explored many of those interactions here and we’re always on the lookout for new and different ways people communicate their data and the insights therein. A few weeks ago we wrote up a short “how to” post describing a recent phenomenon on Twitter – sparktweets. It didn’t take too long before we started seeing the Quantified Self community using these new “data words.”
— P.G. Holder (@pat_holder) April 16, 2013
— Benny Wong (@bdotdub) April 14, 2013
We couldn’t stop thinking about sparktweets. What kind of data could you communicate in 140 characters? What would people do if it was easier to make a sparktweet? So we asked out friend Stan James to help us out and our Sparktweet Tool was born. Since then we’ve seen some great tweets roll though our feed, and we would love to see more. Need some inspiration? Here’s a few we really enjoyed:
▄▃▄▃█▁█▁█▁█ My heart when I walked up to her door, 13 years ago today. (quantifiedself.com/sparktweet-too…)
— Gary Wolf (@agaricus) April 30, 2013
— Robby Macdonell (@robby1066) May 1, 2013
— Martin Putniorz (@sputnikus) May 2, 2013
— BuildingIoT (@BuildingIoT) May 2, 2013
Update: Want to make your own Sparktweet? We made a simple tool that you can use. Check it out here!
I was stumbling around Twitter the other day when I was confronted with something new and different:
— Steve Cavendish (@scavendish) April 5, 2013
Apparently that little data representation is not all that new and different. Way back in 2010 Alex Kerin figured out that Twitter was accepting unicode and decide to play around and see if it could represent data. Lo and behold it could and a SparkTweet was born:
▁▁▂▂▃▄▄█▁▁▂ ▃▄▄▅▆▁▁▂▂▃▄▄▅▆▁▁▂▂▃▄▄▅▆ Can you guess what I’m coding in Excel? Eh? Eh?
— Alex Kerin (@AlexKerin) June 9, 2010
Before we get into how you too can start populating your Twitter feed and Facebook (I checked and it worked there as well) with representations of your own Quantified Self data let’s dive into some history.
a small intense, simple, word-sized graphic with typographic resolution. Sparklines mean that graphics are no longer cartoonish special occasions with captions and boxes, but rather sparkline graphic can be everywhere a word or number can be: embedded in a sentence, table, headline, map, spreadsheet, graphic.
In another wonderful book, The Visual Display of Quantitative Information, Tufte describes sparklines as “datawords: data-intense, design-simple, word-sized graphics.“ Of course, those of us in the QS community are deeply interested not only in data, but also in how data operates in society, what is means as a cultural artifact that is discussed and exchanged in language both written and verbal. This interest iswhat initially piqued my curiosity. The movement of data and a dataword distributed among text and publicly expressed in a tweet. I can’t help but wonder, what does this mean for how we think about and express data about our world?*
If you want display quantitative data in your Twitter stream it shouldn’t take you all that long to get started. Lucky for us Alex Kerin has provided a nifty little Excel workbook that will generate the unicode that can be pasted into your tweet. Just download this workbook and follow the simple instructions! Soon you’ll be able to send out tweets just like this:
My 30-day step history: ▄ ▄ ▄ ▅ ▅ ▅ ▄ ▆ ▄ █ █ ▅ ▁ ▃ ▆ ▅ ▁ ▄ ▇ ▃ ▅ ▆ ▂ ▂ ▅ ▃ ▄ ▄ ▅ ▄ #QuantifiedSelf
— Ernesto Ramirez (@eramirez) April 11, 2013
Now you’re ready and able to go forth and tweet your data! If you use a sparktweet to express your Quantified Self data be sure to let us know in the comments or tweet at us with #sparktweet and/or #quantifiedself.
*Of course the use of sparktweets is not without controversy in the world of data visualization. For more discussion on sparktweets and their utility I suggest you start here.
On Tuesday March 12, Nick Dawson asked if there was a Quantified Self Twitter Chat. Lots of interest followed so we decided to make it happen. We had the very first #qschat twitter chat last Thursday and it was a lot of fun. I learned a lot about what people are thinking and doing in the Quantified Self space and in their daily lives. I’ve included some highlights from the chat below, but you can always just search Twitter for #qschat for the full list of tweets.
We’re going to try our best to make this happen every Thursday night at 6PM PST. Just follow the Quantified Self Twitter account to join in!
Our three questions for tonight (3/22/12) will be:
- What is one thing you’ve learned from your self-tracking and Quantified Self practice?
- Have you ever shared your experiments and results with anyone? If so how did it go. If not, why not?
- Health is an obvious Quantified Self area of interest. What other areas have you applied, or want to apply, Quantified Self to?
Again, join us at 6 PM PST to talk about these three questions and more!
Read more to see some selected tweets from our first chat last Thursday!
Denis Harscoat is the founder of Quantter and co-organizer of the London Quantified Self group and the new Paris QS group. He and co-founder Francis Dierick noticed people quantifying their activites on Twitter, and created a simple way to gather this data together. In the video below, Denis takes us on a tour of Quantter – leveraging Twitter hashtags to help people track their daily activities, receive motivating cheers from their friends, and help them reach their goals. Quantter is also a proud sponsor of the Quantified Self Conference in May, so you can meet Denis and Francis there! (Filmed at the Amsterdam Quantified Self meetup held at Mediamatic).
From the London QS Show&Tell meetup group: Kiel Gilleade talks about his experiences with tracking his heart rate 24×7 and sharing it in real-time via the Internet. More information about the project can be found at Kiel’s Physiological Computing Site and at his BodyBlogger Twitter stream. Watch the video below to hear Kiel talk about the interesting social ramifications of continuous heart rate tracking, and what he has learned about alcohol, sleep, and stress.