[Air-L] Research on Twitter - a couple of questions
u.reips at ikerbasque.org
Tue Jan 17 05:16:54 PST 2012
Hi Monica and all:
I agree entirely with Sava's answers.
Furthermore it is important to know that there are two sources of
geolocation information one can tap into: geotagged tweets versus
profile-based location. Sarita's e-mail below addresses the problems
with the latter source.
The vast difference in reliability of the two sources of geolocation
information imho needs to be addressed in any serious research using
Twitter data. Here a quote from our own Twitter paper: "The iScience
API that is used in Global Search ... shows geotagged tweets only
(i.e., there is no profile-based location inference)."
Feel free to download our paper, it is #92 on
Our Web service is at http://tweetminer.eu
At 7:34 Uhr -0500 17.1.2012, Sarita Yardi wrote:
>This paper can probably answer some of your questions.
>Abstract: "Little research exists on one of the most common, oldest, and
>most utilized forms of online social geographic information: the "location"
>field found in most virtual community user profiles. We performed the first
>in-depth study of user behavior with regard to the location field
>in Twitter user profiles. We found that 34% of users did not provide real
>location information, frequently incorporating fake locations or sarcastic
>comments that can fool traditional geographic information tools. [....]"
>School of Interactive Computing
>Georgia Institute of Technology
>On Tue, Jan 17, 2012 at 12:29 AM, Monica Barratt <tronica at gmail.com> wrote:
>> Dear AoIR members
>> Recently there have been more scholarly articles published using
>> Twitter data in the health field. I've found myself as a peer-reviewer
>> of one such article. In case the authors happen to be subscribed, I'll
>> keep the exact topic quiet... but basically what the authors are doing
>> is using Twitter's advanced search function to compile a database of
>> Tweets which they then subject to a simple content analysis.
>> I have done my own research and discussed the issue with local expert
>> Axel Bruns, however I'm still a bit unclear on a couple of points, and
>> wondered if anyone reading could assist me:
>> 1. The authors draw samples of Tweets over a specific time frame from
>> specified US cities. They appear to assume that by using the advanced
>> search option 'Near this place' and entering the city name will bring
>> up all tweets from that city or surrounds (see
>> https://twitter.com/#!/search-advanced ). But wouldn't that only bring
>> up the tweets from people who have nominated their home city or
>> geolocated their tweets? Don't many users do neither of these things
>> and therefore the corpus of data would be incomplete?
>> Can anyone verify this ... and also does anyone know if there is any
>> research on the proportion of Twitter users whose location would be
>> known and therefore would be included in such a dataset?
>> 2. The authors use profile images to ascertain the approximate age and
>> gender of account holders. In my experience, many people use profile
>> images that do not represent themselves - eg. celebrities or past
>> images of themselves or images of themselves with others.
>> Is this an accurate or useful way of dealing with Twitter profile data
>> or is it too flawed as a technique to be useful?
>> While I'm not an expert in Twitter research, it seems to me that
>> Twitter research is on more solid ground when using a hashtag to
>> identify a corpus of Tweets, as this is the method Twitter users
>> employ too.
>> Thanks for your thoughts/help
>> Research Fellow @ National Drug Research Institute, Curtin University
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