[Air-L] additional suggestions for Twitter aggregating & analytic tools

[Maurice Vergeer]

correct. There was Twapperkeeper which has become Hootsuite. This is
YourTwapperkeeper, the open source version (see
http://mappingonlinepublics.net/2011/06/21/switching-from-twapperkeeper-to-yourtwapperkeeper/
)

best regards
Maurice

On Mon, Oct 1, 2012 at 2:45 PM, Siapera, Eugenia (Dr.) <
es107 at leicester.ac.uk> wrote:

> Great thread and very useful for some of us - however, I am slightly
> confused re Twapperkeeper - I was under the impression that it got sold to
> Hootsuite and is no longer available to download-use?
>
> ________________________________________
> From: air-l-bounces at listserv.aoir.org [air-l-bounces at listserv.aoir.org]
> On Behalf Of Maurice Vergeer [m.vergeer at maw.ru.nl]
> Sent: 30 September 2012 21:59
> To: air-l at listserv.aoir.org
> Cc: eciszek at uoregon.edu; a.bruns at qut.edu.au
> Subject: Re: [Air-L] additional suggestions for Twitter aggregating &
> analytic tools
>
> Axel Bruns beat me to it. Yes, I would advise YourTwapperkeeper for data
> collection as well. I've been using it for a while and am very pleased with
> it. Things are indeed very well described in the First Monday manuscript:
>
> http://firstmonday.org/htbin/cgiwrap/bin/ojs/index.php/fm/article/viewArticle/3937/3193
>
> As for handling the data, I prefer to use SPSS. Yes, a statistical tool.
> But I use it primarily to handle the data. Also I use SPSS to match
> external data to the Twitter data. The data Twitter provides are of course
> somewhat limited. However if one taps into external data sets one is able
> to enrich Twitter data for more advanced analyses.
>
> Also, SPSS has recently incorporated many text handling features to create
> new variables based on text strings. It thus also allows for creating your
> own metrics because - as Axel Bruns states - Twitter's metrices are biased.
> See my blogpost:
> http://blog.mauricevergeer.nl/2011/04/18/bias-in-twitter-api-measurements/
>
> As for Big Data analysis: without going for the Big Data, the number of
> observations already increases rapidly anyhow. See my presentation held at
> WAPOR Amsterdam:
>
> http://www.slideshare.net/maver/candidates-communication-patterns-on-twitter
> .
> SPSS can easily handle large amounts of data.
> As for large networks, I would recommend Pajek:
> http://mrvar.fdv.uni-lj.si/pajek/. They even released another version
> Pajek
> XXL for very very large networks.
>
> Finally I know R the statstical / programming software also has a Twitter
> package (http://cran.r-project.org/web/packages/twitteR/index.html). Have
> tried it once, but because I am noy (yet) an R-expert haven't used it since
> then. The advantage of using it in R would be that one cold stay within a
> single software environment. R also has text (
> http://gking.harvard.edu/readme) and several network analytical packages.
>
> HTH
> Maurice
>
>
> .
>
>
>
>
> ___________________________________________________________________
> Maurice Vergeer
> To contact me, see http://mauricevergeer.nl/node/5
> To see my publications, see http://mauricevergeer.nl/node/1
> ___________________________________________________________________
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-- 
___________________________________________________________________
Maurice Vergeer
To contact me, see http://mauricevergeer.nl/node/5
To see my publications, see http://mauricevergeer.nl/node/1
___________________________________________________________________