{"id":1801,"date":"2012-09-29T10:52:38","date_gmt":"2012-09-29T00:52:38","guid":{"rendered":"http:\/\/mappingonlinepublics.net\/?p=1801"},"modified":"2012-09-29T10:59:02","modified_gmt":"2012-09-29T00:59:02","slug":"a-quick-recap-of-twitter-research-approaches","status":"publish","type":"post","link":"https:\/\/mappingonlinepublics.net\/dev\/2012\/09\/29\/a-quick-recap-of-twitter-research-approaches\/","title":{"rendered":"A Quick Recap of Twitter Research Approaches"},"content":{"rendered":"

Any self-respecting Internet researcher will already be aware that the Association of Internet Researchers<\/a> (AoIR) is the<\/em> place to keep track of what\u2019s cutting edge in the field. On the AoIR mailing-list<\/a>, there\u2019s been an interesting discussion over the last few days about the available tools for tracking, capturing, and analysing Twitter<\/em> data<\/a> \u2013 and since nobody had yet mentioned yourTwapperkeeper<\/em> as a useful solution for many standard tasks, I\u2019ve just posted an overview of how we\u2019ve been approach such research.<\/p>\n

As I haven\u2019t had much time recently to post many updates on this Website about our methodological work, I thought I\u2019d cross-post my message to the mailing-list here. For those who\u2019ve come to Mapping Online Publics<\/em> only recently, perhaps it also provides a useful summary of where we\u2019re at so far.<\/p>\n

 <\/p>\n

Erica Ciszek asked:<\/p>\n

> I was wondering if anyone can suggest particular tools for aggregating and
\n> analyzing Twitter content.<\/p><\/blockquote>\n

Maybe I\u2019m old-school on this, but I’m surprised no-one’s mentioned yourTwapperkeeper<\/em> yet \u2013 in my experience, very straightforward to set up (all you need is a standard LAMP server setup to run it on), and fine for most standard Twitter<\/em> capture tasks (e.g. tracking hashtags, keywords, specific users, etc.). It\u2019s open source and available here:<\/p>\n

https:\/\/github.com\/jobrieniii\/yourTwapperKeeper<\/a><\/p><\/blockquote>\n

We\u2019ve made some modifications to more easily export datasets in CSV\/TSV-format datasets \u2013 see details here:<\/p>\n

http:\/\/mappingonlinepublics.net\/2012\/01\/09\/twapperkeeper-and-beyond-a-reminder\/<\/a><\/p><\/blockquote>\n

Personally, I don\u2019t trust most out-of-the-box Twitter<\/em> analytics tools, and prefer to roll my own \u2013 for processing CSV\/TSV datasets containing Twapperkeeper<\/em>-format data, I\u2019ve been using the scriptable command-line tool Gawk<\/em> with great success. A collection of Gawk<\/em> scripts for standard Twapperkeeper<\/em> data processing tasks is available under a Creative Commons licence here:<\/p>\n

http:\/\/mappingonlinepublics.net\/2011\/06\/22\/gawk-scripts-for-processing-twitter-data-vol-1\/<\/a><\/p><\/blockquote>\n

Additionally, my \u2018Swiss army knife\u2019 Gawk<\/em> script for extracting activity metrics from a Twapperkeeper<\/em> dataset is here:<\/p>\n

http:\/\/mappingonlinepublics.net\/2012\/01\/31\/more-twitter-metrics-metrify-revisited\/<\/a><\/p><\/blockquote>\n

The question of developing standard, case-independent metrics for the description of Twitter<\/em> activity patterns is something Stefan Stieglitz and I are taking up in two forthcoming papers (happy to share drafts \u2013 email me off-list). The keynote which Jean Burgess and I presented at the recent Conference on Science and the Internet foreshadows some of this discussion, though:<\/p>\n

Axel Bruns and Jean Burgess. \u201cNotes towards the Scientific Study of Public Communication on Twitter.<\/a>\u201d Keynote presented at the Conference on Science and the Internet, D\u00fcsseldorf, 4 Aug. 2012. (The slides and video of the presentation are here: http:\/\/snurb.info\/node\/1678<\/a>.)<\/p><\/blockquote>\n

Detailed notes on how we use these scripts to process Twitter<\/em> data, and additional processing tools, are also on our Website \u2013 see http:\/\/mappingonlinepublics.net\/category\/twitter\/<\/a> for more.<\/p>\n

For network visualisation, I recommend the open source software Gephi<\/em>. My article in Information, Communication & Society<\/em> describes how I\u2019ve used yourTwapperkeeper<\/em>, Gawk<\/em> and Gephi<\/em> to create dynamic visualisations of Twitter<\/em> conversation networks:<\/p>\n

Axel Bruns. \u201cHow Long Is a Tweet? Mapping Dynamic Conversation Networks on Twitter Using Gawk and Gephi.\u201d Information, Communication & Society<\/em>, 17 Nov. 2011. http:\/\/dx.doi.org\/10.1080\/1369118X.2011.635214<\/a><\/p><\/blockquote>\n

For more sophisticated, \u2018big data\u2019 research (i.e. upwards of a few million tweets per dataset), the yourTwapperkeeper<\/em> approach is less useful (the LAMP framework just isn’t built for big data), and you\u2019ll probably need to build your own customised solution. Eugene Liang and I discuss the pros and cons of both approaches in a recent article in First Monday (while we frame this in a crisis communication context, the discussion applies well beyond this):<\/p>\n

Axel Bruns and Yuxian Eugene Liang. \u201cTools and Methods for Capturing Twitter Data during Natural Disasters.<\/a>\u201d First Monday<\/em> 17.4 (2012).<\/p><\/blockquote>\n

Hope that helps.<\/p>\n

<insert obligatory plug for the \u201cDigital Data \u2013 Lost, Found, and Made<\/a>\u201d panel at the upcoming AoIR conference<\/a>, where I’m sure we can discuss the question of Twitter<\/em> research methods some more as well><\/p>\n","protected":false},"excerpt":{"rendered":"

Any self-respecting Internet researcher will already be aware that the Association of Internet Researchers (AoIR) is the place to keep track of what\u2019s cutting edge in the field. On the AoIR mailing-list, there\u2019s been an interesting discussion over the last few days about the available tools for tracking, capturing, and analysing Twitter data \u2013 and … <\/p>\n

Continue reading “A Quick Recap of Twitter Research Approaches”<\/span><\/a><\/p>\n

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