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There are some issues concerning Twitter data you probably should take
account of.
for instance, think of setting a time frame for the tweets. As you may
know there is a limit of 3200 tweets to download. An active ministry
may have more than that whereas an inactive one may have very few. My
suggestion is to create new variables such as number of tweets per day
or tweets per month. This way the tweet activity is more comparable.
To do this accurately you need to determine what twitteraccount has
the latest first tweet in your data (i.e. the first tweet of the
3200). That will be the time frame that is comparable for all.
As for network size (follower and following) you need to account for
when the account was created. Because Twitter networks tend to grow
over time, fresh account have small networks wehereas old twitter
accounts may have larger ones. Comparing without the age of the
twitter account may lead to false conclusions.
As for sampling, why would you want to? Apart from the timeframe for
the tweet analysis there is probably no need for this. When using SPSS
(or any other statistical package) for t-tests and correlations
170.000 will be no problem computationally.

best wishes
Maurice Vergeer



On Mon, Dec 5, 2011 at 6:09 AM, G.F.Khan <[log in to unmask]> wrote:
> ***** To join INSNA, visit http://www.insna.org ***** Hi all,
>
> I have Twitter data (i.e. followings, followers, Tweets, etc) for three
> countries' ministries (at least 35 ministries from each country). I am
> interested to check if the three countries differ statistically in terms of
> followings, followers, and Tweets. Which test should I be running? Can I
> also conduct some correlations analysis on this data, for example,
> correlation between followers and Tweets?
>
> Second, what kind of sampling strategy would you recommend to select a
> representative sample from the tweets for conducting semantic analysis?
> (Combined tweets of all the ministries are more than 170,000).
>
> Thank you for help in advance.
>
> --
> Gohar Feroz khan, PhD
> Dept. of Media & Communication, YeungNam University,
> 214-1, Dae-dong, Gyeongsan-si, Gyeongsangbuk-do,
> South Korea, Zip Code 712-749
> Mobile: +82-10-5510-8071
> [log in to unmask]
> Research: http://laton.wikispaces.com/Dr.+Khan
> Class Wiki: http://onlinejournalism.wikispaces.com/;
> http://uandi.wikispaces.com/Syllabus;
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-- 
___________________________________________________________________
Maurice Vergeer
Department of communication, Radboud University  (www.ru.nl)
PO Box 9104, NL-6500 HE Nijmegen, The Netherlands

Visiting Professor Yeungnam University, Gyeongsan, South Korea

Recent publications:
-Vergeer, M. Lim, Y.S. Park, H.W. (2011). Mediated Relations: New
Methods to study Online Social Capital. Asian Journal of
Communication, 21(5), 430-449.
-Vergeer, M., Hermans, L., & Sams, S. (forthcoming). Online social
networks and micro-blogging in political campaigning: The exploration
of a new campaign tool and a new campaign style. Party Politics.
-Pleijter, A., Hermans, L. & Vergeer, M. (forthcoming). Journalists
and journalism in the Netherlands. In D. Weaver & L. Willnat, The
Global Journalist in the 21st Century. London: Routledge.
-Vergeer, M., Eisinga, R. & Franses, Ph.H. (forthcoming). Supply and
demand effects in television viewing. A time series analysis.
Communications - The European Journal of Communication Research.

Webspace
www.mauricevergeer.nl
http://blog.mauricevergeer.nl/
www.journalisteninhetdigitaletijdperk.nl
maurice.vergeer (skype)
@mauricevergeer (twitter)
___________________________________________________________________

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