Tweets are Not Created Equal. Intersecting Devices in the 1% Sample
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Carolin Gerlitz & Bernhard Rieder IR15 - Boundaries & Intersections October 23, 2014 Tweets are Not Created Equal Intersecting Devices in the 1% Sample
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Presentation by Carolin Gerlitz and Bernhard Rieder at the AoIR conference in Daegu, South Korea on October 23, 2014
Transcript of Tweets are Not Created Equal. Intersecting Devices in the 1% Sample
Carolin Gerlitz & Bernhard RiederIR15 - Boundaries & IntersectionsOctober 23, 2014
Tweets are Not Created EqualIntersecting Devices in the 1% Sample
Digging deeper into Twitter devices
The Twitter API's 1% random sample can be used to explore, baseline, contextualize, verify, etc. (Gerlitz & Rieder 2013, Morstatter et al. 2014).
How can we qualify individual elements in relation to a larger platform ecology?
The presentation inquires more deeply into the role devices play on Twitter.
We used a week-long random sample of tweets to further explore this aspect. (14.6.2014 - 20.6.2014, n = 31.707.162)
Devices intersect use practices
There has been a proliferation of very different devices (mobile, desktop, web, buttons, bots, etc.) from which people send their tweets. It's full of devices!
Thinking Twitter as ecology of connected devices, we ask (1) how we can qualify devices and (2) how devices can enable us to unpack metrics for studying use cultures.
Frequency based metrics suggest that the units they count are equivalent (e.g. tweets per time for a certain hashtag).
Do we need to conceptualize devices as intervening variables?
iPhone
Tweetdeck
Web client
Tweetadder
Instagram Tribez
iPhone
Tweetadder
Tweetadder
Hashtag qualification#iraq
Hashtag qualification#CallMeCam
Hashtag qualification#gameinsight
Hashtag qualification#love
Devices & use practices
Desktop clients (Web, Tweetdeck, etc.) are overrepresented in news conversations; Tweetdeck also points towards professional social media practices.
The iPhone is the preferred microphone of the American teenager.
Custom autopost clients (platforms, games, etc.) are engaged in activity loops.
Automation clients (dlvr.it, IFTT, or Tweetadder) empower promotion, spam, hijacking, and syndication practices.
Different devices have different capacities and enable different ways of engaging with the Twitter platform (posting, observing, responding, etc.).
Domain qualificationnytimes.com
Domain qualificationyoutube.com
Domain qualificationetsy.com
Devices intersect practices
Tweets are not created equal. Devices imply different regimes of "being on Twitter" that are caught up in different perspectives, purposes, and politics.Twitter takes part in complex platform ecologies that mediate tweeting in different ways and are thus co-constitutive of practices. Devices intersect practices.
For Internet researchers, this creates problems and opportunities. Devices as intervening variables can both skew and explain.
Frequency counts that do not take into account devices are problematic: do 100K tweets from Tweetadder "mean" or "indicate" the same thing as 100K sent from the iPhone? They refer to different populations, practices, purposes, and politics.
Conclusion
Devices need to be taken into account when sampling, cleaning, analyzing, and interpreting Twitter data.
Frequency counts are not comparable from the outset, but need to be made comparable by including devices in the interpretation.
This kind of unpacking and repacking of components in the platform ecologies can be performed for various other elements. (cf. Bruns & Stieglitz 2013)
DMI-TCAT (Borra & Rieder 2014), open source, available at:https://github.com/digitalmethodsinitiative/dmi-tcat
Thank you.
Carolin Gerlitz, [email protected], @cgrltzBernhard Rieder, [email protected], @riederb
