Hi Nathan,
Take a look at the attached - has a lot of keywords. Haven't gone through
it in detail but wanted to send it to you quickly in case you are getting
ready to run your queries. Brian, we should update our spreadsheets..
Naren
---------- Forwarded message ---------
From: Mares, David
Date: Thu, Nov 17, 2022 at 1:27 AM
Subject: Re: update
To: naren@cs.vt.edu
Cc: Brian Mayer
Naren and Brian,
Please find attached a file with my additional words. I also found an
article, with its supplementary material, that discusses predictive
analysis for humanitarian aid and relief groups who need to be prepared for
sudden flows of refugees and internally displaced persons. I'm attaching
that material because it will be helpful in writing up the initial report
to ODNI about whatever results you get and the potential of retooling
EMBERS for migrant surges in the Western Hemisphere.
Finally, I'm attaching some materials to demonstrate how the IOM
(International Office on Migration) is pulling together
daily/weekly/monthly data on migratory flows.
I'll work on the annotated short bibliography next. If you need me to do
anything else, just let me know.
Good luck,
David
------------------------------
*From:* Mares, David
*Sent:* Monday, November 14, 2022 12:26 PM
*To:* naren@cs.vt.edu
*Cc:* Brian Mayer
*Subject:* Re: update
Thanks for the clarifications, Naren. I'll get back to work on this today.
David
------------------------------
*From:* Naren Ramakrishnan
*Sent:* Saturday, November 12, 2022 5:05 AM
*To:* Mares, David
*Cc:* Brian Mayer
*Subject:* Re: update
Thank you very much David - very very useful!
Reg your comment that we are looking for primarily surges of migration -
that is true, in that ODNI would like to be ready for a sudden surprise but
they are also interested in the total count(s) of people - but we will be
able add a default baseline value to a surge-predicted value, to get this
total count.
We do have multiple news sources and we will get to separating them into
country of origin (I am sure we likely have that information) so that as
you say we can separate out the context in which specific keywords are
used. This will be done using our geolocator. For now we want to use
keywords to net a broad collection of articles and then we can distinguish
the contextual information in which different keywords are used. So we can
think of this stage as a very broad/weak signal just to make sure we don't
lose anything that could be relevant later on.
We will add these words to our list - please do let us know if there are
other push/pull - and also transit issues as you mentioned. Thanks a lot!
Naren
On Sat, Nov 12, 2022 at 12:54 AM Mares, David wrote:
Naren and Brian,
I've been reading and conceptualizing the task and reviewing the current
spreadsheet.
We are focusing on *sudden forced migration*, or *migration **surges **NOT*
on migration per se or long-term migration dynamics. We can think in terms
of ‘triggers’, as we did with civil unrest.
The ‘triggers’ are highly likely to be context-dependent and if we only
have one data source (major newspapers in English and Spanish?) that could
overwhelm the specific context and give us no correlation – e.g., in Costa
Rica a proliferation of the words “Cubans”, “Venezuelans” “Nicaraguans” or
“Haitians” is likely to refer to the large influx of refugees and irregular
migrants so that would be useful to track. But if we can’t separate out the
Costa Rican context, then any payoff to us will be overwhelmed by the
general use of these words in non-Costa Rican related news stories.
The words in the attached file are my initial take. A few of them are
already included in the current spreadsheet, but most are not. Before
pursuing this line of work, I thought it would be best to get your feedback.
Thanks,
David
------------------------------
*From:* Naren Ramakrishnan
*Sent:* Wednesday, November 9, 2022 1:53 PM
*To:* Mares, David ; Brian Mayer
*Subject:* Notes from today's call
Hi David,
So great catching up with you today! Below are the notes from the call.
Brian, can you share the current spreadsheet with David?
Best,
Naren
- proportion of minor, timing, origin/destination
- push/pull factors, transit issues, blockages
- lots of literature: sending and receiving communities
- less chaos in these flows than we think, lots more organization and
communication. These are high risk movements, they don’t do it willy nilly.
- various types of triggers: Salvadorian govt gets into a confusion with US
government, so it doesn’t do as much as it has done to curb migrants
- keywords: not only in push and pull factors but also in transit arena.
- pull factors: jobs, job opportunities, benefits (does not payout as a big
attraction) eg CA would permit DACA students to remain in the University
system, community ties (people in communities that have ties back to
communities in Mexico/Nicaragua), community contacts that help people get a
job..
- push factors: convince people to undertake the voyage that has associated
range of costs, local violence (targeted violence toward particular
communities, e.g., drug gangs shooting not just mayor but also school
principal), economic collapse, natural resource issues
--
Naren Ramakrishnan
https://urldefense.com/v3/__http://people.cs.vt.edu/*naren/__;fg!!Mih3wA!Bvk...
Thomas L. Phillips Professor of Engineering
Director, Sanghani Center for AI and Data Analytics
https://urldefense.com/v3/__https://sanghani.cs.vt.edu__;!!Mih3wA!Bvk3pRaHoJ...
Director, NSF NRT UrbComp
https://urldefense.com/v3/__https://sanghani.cs.vt.edu/academics/urban-compu...
Department of Computer Science, Virginia Tech
On Twitter as @profnaren
--
Naren Ramakrishnan http://people.cs.vt.edu/~naren/
Thomas L. Phillips Professor of Engineering
Director, Sanghani Center for AI and Data Analytics
https://sanghani.cs.vt.edu
Director, NSF NRT UrbComp
https://sanghani.cs.vt.edu/academics/urban-computing/
Department of Computer Science, Virginia Tech
On Twitter as @profnaren
