[Air-L] Methods to infer Twitter data location

[Shulman, Stu]

User location on Twitter is very tricky and unreliable. Users must opt-in
to share geo or to "claim" a location when they set up or edit their
account profile. Claims of location range from 100% authentic to
preposterous satirical banter and everything in between. Generally, if you
restrict yourself to the study geo-located or location-purported data, you
are looking at a small fraction of the whole dataset. For example, here are
the top most common 30 "claimed" locations in a dataset of Tweets about
"Dominion Voting Systems" from November 2020 where the most common from
421,000 Tweets is 15,000+ (United States) and the 30th is almost 700 (New
York, NY). There are 239,051 purported locations in this dataset.

United States
USA
Texas, USA
Florida, USA
California, USA
Texas
Georgia, USA
Canada
Venezuela
New York, USA
Pennsylvania, USA
Arizona, USA
Los Angeles, CA
Michigan, USA
Ohio, USA
North Carolina, USA
Florida
New Jersey, USA
Washington, DC
Houston, TX
Virginia, USA
California
Tennessee, USA
South Carolina, USA
Atlanta, GA
Washington, USA
Earth
Illinois, USA
Chicago, IL
New York, NY

To study data like this you may need to concatenate things that are similar
but the same in practice at the geographical scale you are working with.
Some locations are just Twitter handles. Others are Gab or Parler handles.
Some look like this:

A Desk in Open Office Hell
A Field of White Roses
A Galaxy Far Away
A Galaxy far far away
A Galaxy far, far South
A Garden of Feelings &Hot Air
A Getsemani, Jerusalen


On Wed, Feb 22, 2023 at 11:32 AM Deena Abul-Fottouh via Air-L <
air-l at listserv.aoir.org> wrote:

>    Hi aoir,
>
>    Could anyone please share resources on methods/applications to infer
>    Twitter data locations from non-geo-located messages?
>
>    Thanks.
>
>    Deena
>
>    ____________________________
>
>    Deena Abul-Fottouh, PhD.
>
>    Postdoctoral Research Fellow
>
>    Digital Society Lab
>
>    Political Science Department
>
>    Phone icon t phone: [1](905) 525-9140
>    Envelope icon email: [2]abulfodm at mcmaster.ca
>
>    McMaster University
>
>    1280 Main Street West
>
>    Hamilton, ON L8S 4M4
>       McMaster University Brighter World logo
>
> References
>
>    1. tel:+19055259140
>    2. mailto:abulfodm at mcmaster.ca
> _______________________________________________
> The Air-L at listserv.aoir.org mailing list
> is provided by the Association of Internet Researchers http://aoir.org
> Subscribe, change options or unsubscribe at:
> http://listserv.aoir.org/listinfo.cgi/air-l-aoir.org
>
> Join the Association of Internet Researchers:
> http://www.aoir.org/
>


-- 
Dr. Stuart W. Shulman
Founder and CEO, Texifter
Editor Emeritus, *Journal of Information Technology & Politics*