Comments on: Playing with algorithms 3: But what about Twitter? https://edc15.education.ed.ac.uk/kfirth/2015/03/15/playing-with-algorithms-3-but-what-about-twitter/ Another Education and digital culture 2015 site Mon, 30 Mar 2015 21:05:41 +0000 hourly 1 https://wordpress.org/?v=4.2.38 By: Katherine https://edc15.education.ed.ac.uk/kfirth/2015/03/15/playing-with-algorithms-3-but-what-about-twitter/#comment-443 Sun, 22 Mar 2015 02:29:21 +0000 http://edc15.education.ed.ac.uk/kfirth/?p=355#comment-443 Okay, did some research (my two blogs are now the top results for that search term!).

Most of all, mobile users are usually in a different frame of mind than desktop users. We can’t really make any precise assumptions about the context of the device usage, but compared to desktop usage they quite often will be standing up and walking around or driving, and sometimes just scanning their handset or tablet. This might call for less detailed content than what you would use for more focused desktop users. Instead of presenting all of the day’s news items, for example, tracking unread items or the most popular trending items might be more important. Users might also want different content depending on their location.Smashing Magazine

Interestingly, this suggests that mobile users might want more “popular trending items” rather than less.

But the article goes on to say:

Other times, such as when waiting for a connecting flight, mobile users will have more time on their hands and attention to spare.

Therefore, the app might be responding to how most people are now using their mobiles (at home, while commuting, with time to spare), or at least how I use my mobile (definitely desktop Twitter is used between other work, where as mobile Twitter is regularly used instead of television as an extended leisure activity).

]]> By: Katherine https://edc15.education.ed.ac.uk/kfirth/2015/03/15/playing-with-algorithms-3-but-what-about-twitter/#comment-442 Sun, 22 Mar 2015 02:19:17 +0000 http://edc15.education.ed.ac.uk/kfirth/?p=355#comment-442 Thanks Jeremy!
That’s a good question. My guess is that, based on more limited data, Twitter is not going to personalise it’s curation quite so individually. Instead, it will make assumptions that I will behave like ‘most’ people. Popularity therefore is going to be significant–‘lots of people like this, so you are more likely like this’. This is a reasonable assumption to make for a generic user.
The app, on the other hand, is able to weigh up more data points (for me, because of how I use it), and therefore was able to be more specific. Because I have a lot of niche interests, the distinction is visible on my two timelines. If I engaged more with popular tweets, I doubt that would have been so clear.
That’s my guess, but I’m about to go off and do some more research, as Ed suggests!

]]> By: Katherine https://edc15.education.ed.ac.uk/kfirth/2015/03/15/playing-with-algorithms-3-but-what-about-twitter/#comment-441 Sun, 22 Mar 2015 02:13:03 +0000 http://edc15.education.ed.ac.uk/kfirth/?p=355#comment-441 Thanks PJ, I really appreciate it! I’m enjoying including more food!

]]> By: Katherine https://edc15.education.ed.ac.uk/kfirth/2015/03/15/playing-with-algorithms-3-but-what-about-twitter/#comment-440 Sun, 22 Mar 2015 02:12:32 +0000 http://edc15.education.ed.ac.uk/kfirth/?p=355#comment-440 Woah! That’s very surprising! thanks Ed!
Yes, I suspect that geolocation data would be used, but I live pretty close to where I work, so I wouldn’t expect that to factor in the differences.
I’d be interested in what the differences are between typical desktop and mobile use (I would assume something to do with ‘work’ vs ‘leisure’, but I’ll have to search!).

]]> By: Ed Guzman https://edc15.education.ed.ac.uk/kfirth/2015/03/15/playing-with-algorithms-3-but-what-about-twitter/#comment-424 Wed, 18 Mar 2015 06:26:39 +0000 http://edc15.education.ed.ac.uk/kfirth/?p=355#comment-424 A pie for PI day, looks delish! Twitter also captures geolocation data, although this may be not necessarily be factored in for the discovery timeline. The differences in desktop and mobile timelines suggest that Twitter also makes assumptions about how people interact with content based on devices (desktop or mobile) . I think you’ve uncovered many interesting things here. In fact, when I googled for “twitter discovery timeline algorithm” this page was in the top 10 results.

]]> By: PJ Fameli https://edc15.education.ed.ac.uk/kfirth/2015/03/15/playing-with-algorithms-3-but-what-about-twitter/#comment-423 Tue, 17 Mar 2015 12:57:58 +0000 http://edc15.education.ed.ac.uk/kfirth/?p=355#comment-423 Katherine, yours is definitely the most ‘appetizing’ blog site. A very instructive and informative series of blogs with analysis and synthesis on Twitter, tweets and tweeting. I am still coming to grips with Discovery timeline and Twitter audit that you’ve introduced. Cheers, PJ

]]> By: Jeremy Knox https://edc15.education.ed.ac.uk/kfirth/2015/03/15/playing-with-algorithms-3-but-what-about-twitter/#comment-413 Sun, 15 Mar 2015 11:23:50 +0000 http://edc15.education.ed.ac.uk/kfirth/?p=355#comment-413 Really great ‘reverse engineering’ of the Twitter timeline Katherine.

‘Of the tweets in the desktop Discovery timeline, 5 had a high retweet count (66-197)’

So, in other words, the assumption here is that popular tweets are going to be more important and relevant to you? Is that the case? Why would Twitter assume that this *is* important. I wondered if you could say a bit more here about what the implications of you discoveries here might be. You’ve done a great job of exposing the automated processes at work behind the façade of the discovery timeline, but what are the consequences, and how significant are they?

I must have missed Pi day, what a shame…your pie looked rather delicious though.

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