[Air-L] Methods to infer Twitter data location

Thu Feb 23 08:49:09 PST 2023

Actually, I don’t disagree with you Jeff.

If their location is public, then the conditions my comment may not apply. However, it still does in the context/specificity of the original question: inferring tweet location in lieu of geo-tags. Geo-tags are much more specific than a profile’s “City, State/Province.” Even if I had my city publicly available, an extreme inference of location on a tweet might approximate my home, to refer to another comment. Even then, if we are speaking generally and only place users “at home,” the problem remains minimal. However, if the inference is closer to an actual geo-tag than general “place” then it potentially goes beyond what they have made available publicly and increases the linkability of information about users without their consent/knowledge, and depending on the subject of the analysis could potentially cause harm. Technically, our addresses are publicly available if someone is on our street, but sharing that information linked to individuals online can be illegal.

Again, I agree that general, publicly available location information is pretty safe. I simply cautioned that how any data that includes inferred specific locations, as the original question suggested may be a goal, is very likely to have risks that should be mitigated.

Dan

From: Jeff Hemsley <jjhemsle at syr.edu>
Date: Thursday, February 23, 2023 at 5:55 AM
To: Gardner, Daniel <dgardner at chapman.edu>, Libby Hemphill <libbyh at umich.edu>, Shulman, Stu <stu at texifter.com>
Cc: aoir list <air-l at aoir.org>
Subject: RE: [Air-L] Methods to infer Twitter data location
External Message

[External Message]

A while back we used the concept of "Place" from Human Geography in a paper where we used the profile listing of where someone claims to be or be from. I've included the cite for the paper below.

Yes, people do claim to be from Mars sometimes, like Libby says. I expect that is because they wish to preserve privacy or they just enjoy being silly. Both are ok in my book. And like Libby, I think if your methods take into consideration a certain amount of noise, then it should be fine.

Unlike Dan, I'm not to worried about infringing on someone's privacy when using the place they list on their PUBLIC Twitter profile.

Here is the paper I mentioned:
Hemsley, J. J., & Eckert, J. (2014, January). Examining the role of" place" in twitter networks through the lens of contentious politics. In 2014 47th Hawaii International Conference on System Sciences (pp. 1844-1853). IEEE.

-----Original Message-----
From: Air-L <air-l-bounces at listserv.aoir.org> On Behalf Of Gardner, Daniel via Air-L
Sent: Wednesday, February 22, 2023 3:34 PM
To: Libby Hemphill <libbyh at umich.edu>; Shulman, Stu <stu at texifter.com>
Cc: aoir list <air-l at aoir.org>
Subject: Re: [Air-L] Methods to infer Twitter data location

Hi list,

I have been having a nice chat with Deena about this, but given now a few technical responses to this query, I wanted to send to list.

I would urge researchers in this space to make sure they are considering the immediate ethical dimensions of attempting to infer the physical locations of users who have, by their settings and practice explicitly said, "please don't know my location," especially if that location may in fact be their home...

What that location becomes linked to in any data set produced, could potentially be deeply harmful, or at a minimum invasive.

Best of luck,
Dan

From: Air-L <air-l-bounces at listserv.aoir.org> on behalf of Libby Hemphill via Air-L <air-l at listserv.aoir.org>
Date: Wednesday, February 22, 2023 at 12:13 PM
To: Shulman, Stu <stu at texifter.com>
Cc: aoir list <air-l at aoir.org>
Subject: Re: [Air-L] Methods to infer Twitter data location External Message

[External Message]

Depending on your tolerance for error and how specific you need the location to be, you may be able to use the user's location (from their profile, available through the users API if you still have access) rather than the tweet's geolocation. People usually tweet from "home".

Libby

On Wed, Feb 22, 2023 at 2:38 PM Shulman, Stu via Air-L < air-l at listserv.aoir.org> wrote:

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