*** Apologies for multiple posting ***
*Information Retrieval from Microblogs during Disasters (IRMiDis)*
https://sites.google.com/view/irmidis-fire2022/irmidis
Track in conjunction with FIRE 2022 (http://fire.irsi.res.in/fire/2022/home),
December 9-13, 2022, Kolkata (Hybrid Event)
The IRMiDis track aims to develop datasets and methods for solving various
practical research problems associated with a disaster or pandemic
situation. The IRMiDis track has been run successfully with FIRE in the
years 2017, 2018 and 2021.
This year IRMiDis will consist of two important classification tasks over
microblogs/tweets associated with the COVID-19 pandemic:
(1) classifying tweets according to their vaccine-related sentiment
(pro-vaccine, neutral, anti-vaccine)
(2) identifying tweets that mention someone experiencing COVID-19 symptoms,
which is useful for detecting upcoming surges in COVID cases
For both tasks, we will provide training data annotated by human workers,
and test data for evaluating the submitted models.
*All participating teams will get to publish a working notes paper in
the FIRE workshop proceedings. The two best-performing teams in each task
will be awarded winner and runner-up certificates, and their names will be
put up on the track website.*
Training data has already been released. Participating teams need to submit
runs by August 1. More details on how to participate are on the IRMiDis
site: https://sites.google.com/view/irmidis-fire2022/irmidis.
Kind Regards,
*Kripabandhu Ghosh*
Co-organizer
IRMiDis
*** Apologies for cross-posting ***
Dear colleagues,
We have a fully-funded PhD position in the exciting area of Responsible
Natural Language Processing and Machine Learning for Healthcare in the
Amsterdam
UMC <https://www.amsterdamumc.org/en/research.htm> at the University of
Amsterdam <https://www.uva.nl/en>!
Do you have a strong background in NLP and AI, and a keen interest in
applications in healthcare, multilingual language models and model
interpretability? Please consider applying, we are accepting applications
until June 12, 2022!
A few of the exciting projects you can contribute to include developing
technology to predict risk of cancer from patients’ medical notes, and risk
of developing mental disorders from electronic patient records and other
non-clinical data (e.g., social media).
The PhD will be jointly supervised by myself
<https://iacercalixto.github.io/> and prof. Ameen Abu-Hanna
<https://kik.amc.nl/home/aabuhanna/>! Apply here:
https://werkenbij.amsterdamumc.org/en/vacatures/research/phd-natural-langua…
(Please feel free to share with your students/communities)
Have a great week,
Iacer.
*Iacer Calixto* | Assistant Professor of Artificial Intelligence in Medicine
| Department of Medical Informatics, Amsterdam UMC, University of Amsterdam
i.coimbra(a)amsterdamumc.nl | iacer.calixto(a)uva.nl | iacercalixto.github.io.
<http://iacercalixto.github.io/>
Member of the ACL <https://www.aclweb.org/portal/> and the ELLIS Society
<https://ellis.eu/>.
*** Apologies for multiple posting ***
Information Retrieval from Microblogs during Disasters
(IRMiDis)https://sites.google.com/view/irmidis-fire2022/irmidis
Track in conjunction with the Annual Conference of the Forum for
Information Retrieval Evaluation (FIRE 2022 -
http://fire.irsi.res.in/fire/2022/home), December 9-13, 2022, Kolkata
(Hybrid Event)
The Information Retrieval from Microblogs during Disasters (IRMiDis)
track aims to develop datasets and methods for solving various
practical research problems associated with a disaster or pandemic
situation. The IRMiDis track has been run successfully with FIRE in
the years 2017, 2018 and 2021. This year IRMiDis will consist of two
important classification tasks over microblogs/tweets associated with
the COVID-19 pandemic.
*** Task 1: COVID-19 vaccine stance classification from tweets ***
It is important to understand the vaccine-stance of people in order to
nudge people towards intake of COVID vaccines. With this motivation,
this task aims to build an effective 3-class classifier on tweets with
respect to the stance reflected towards COVID-19 vaccines. The 3
classes are:
(1) AntiVax - the tweet indicates hesitancy (of the user who posted
the tweet) towards the use of vaccines.
(2) ProVax - the tweet supports / promotes the use of vaccines.
(3) Neutral - the tweet does not have any discernible sentiment
expressed towards vaccines or is not related to vaccines
*** Task 2: Detection of COVID-19 symptom-reporting in tweets ***
Quickly identifying people who are experiencing COVID-19 symptoms is
important for authorities to arrest the spread of the disease. In this
task, we explore if tweets that report about someone experiencing
COVID-19 symptoms (e.g., 'fever', 'cough') can be automatically
identified. The task is to build an 4-class classifier on tweets that
can detect tweets that report someone experiencing COVID-19 symptoms.
The 4 classes are:
(1) Primary Reporting - The user (who posted the tweet) is reporting
symptoms of himself/herself.
(2) Secondary Reporting - The user is reporting symptoms of some
friend / relative / neighbour / someone they met.
(3) Third-party Reporting - The user is reporting symptoms of some
celebrity / third-party person.
(4) Non-Reporting - The user is not reporting anyone experiencing
COVID-19 symptoms, but talking about symptom-words in some other
context or giving only general information about COVID-19 symptoms.
For both tasks, we will provide training data annotated by human
workers, and test data for evaluating the submitted models. Details of
how to participate are available at
https://sites.google.com/view/irmidis-fire2022/irmidis.
*** Timeline ***
June 6 -- open track website and training data release
July 15 -- test data release
August 1 -- run submission deadline
August 15 -- results declared
September 15 -- Working notes due
October 15 -- Camera ready copies of working notes and overview paper due
*** Organisers ***
Moumita Basu, Amity University Kolkata, India
Soham Poddar, Indian Institute of Technology Kharagpur, India
Saptarshi Ghosh, Indian Institute of Technology Kharagpur, India
Kripabandhu Ghosh, Indian Institute of Science Education and Research,
Kolkata, India
Kind Regards,
*Kripabandhu Ghosh*
Co-organizer
IRMiDis