*ICWSM 2020 Data Challenge - Submission deadline - May 15th 2020*
ICWSM <https://www.icwsm.org/2020/index.html> 2020 is hosting the first
ICWSM data challenge to bring together researchers from across disciplines to
solve societally-relevant problems together as a community. This will be
enabled by fostering collaboration and exchange of ideas in a structured
setting. This year’s data challenge theme is Safety. To achieve this, we
invite participants to work on two pertinent datasets in the areas of
Misinformation
and Abusive behavior in social media.
We invite papers that offer modeling and understanding of misinformation or
abusive behavior based on the datasets we provide, or identify other
important related dimensions to study those two datasets. We welcome
submissions on topics including - but not limited to - the following:
computational models, theories, insights for misinformation/abusive
behavior.
The two datasets were selected after extensive deliberation to meet our
four key criteria:
1.
The dataset should address societally relevant topics of interest to
researchers and practitioners from multiple disciplines,
2.
The dataset should have the ability to answer multiple interesting
questions,
3.
The dataset should have high quality and large quantity of rich data,
and
4.
The dataset should be relatively new.
ICWSM data challenge is a full day workshop taking place on June 8th, 2020
in conjunction with ICWSM 2020, Atlanta, USA. Challenge participants will
have the opportunity to present their work and discuss with other workshop
participants at the workshop.
Workshop URL: https://sites.google.com/view/icwsm2020datachallenge/home
Submission Site: https://easychair.org/conferences/?conf=icwsm2020dc
Important Dates:
-
Data Challenge opens: Feb 21st, 2020
-
Paper Submission deadline - May 15th, 2020
-
Data Challenge notification - May 25th, 2020
-
ICWSM Data Challenge Full day Workshop - June 8th, 2020
Task Description:
Task 1 - The Study of Misinformation in News Articles
This dataset contains 713k articles collected between 02/2018-11/2018,
which were collected directly from 194 news and media outlets including
mainstream, hyper-partisan, and conspiracy sources. It also includes
ground truth ratings of the sources collected from 8 different assessment
sites covering multiple dimensions of veracity, including reliability,
bias, transparency, adherence to journalistic standards, and consumer
trust.
In this task, you are free to use the dataset to a research problem of your
choice. Some examples are: what tactics are used by news producers
publishing false, misleading or propaganda news? How do false news change
over time? Can we build better machine learning algorithms to detect
misinformation? How can models built on this dataset be generalized to
other new articles? We invite papers investigating any related themes here,
and descriptions of running projects and ongoing work in this space.
Dataset link:
https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/ULHLCB
Dataset Paper Reference
Nørregaard, Jeppe, Benjamin D. Horne, and Sibel Adalı. "NELA-GT-2018: A
large multi-labelled news dataset for the study of misinformation in news
articles." In Proceedings of the International AAAI Conference on Web and
Social Media, 2019.
Task 2 - Twitter Abusive Behavior identification
This dataset consists of 100k annotated tweets associated with
Inappropriate speech like abusive and hateful speech, as well as Normal
interactions and Spam. Online social media suffers from many kinds of
abusive behavior such as hate speech, bullying, racism, and sexism.
Identifying abusive behavior will help protect users from harmful content.
This crowd sourced dataset is the end result of a 8-month study of abusive
behavior on twitter.
In this task, you are free to apply the dataset to investigate a research
problem of your choice. Some example applications of this task are:
building better models to identify abusive behavior, providing insights and
research directions in this area, identify other user responses to abusive
content and derive insights into how other users react to abusive behavior
online, identifying intervention mechanisms to detect and mitigate abusive
behavior in the context of online social media. We invite papers
investigating any related themes, and descriptions of running projects and
ongoing work in this space.
Dataset link:
https://www.dropbox.com/sh/4mapojr85a6sc76/AABYMkjLVG-HhueAgd0qM9kwa?dl=0
Dataset Paper Reference
Founta, Antigoni Maria, Constantinos Djouvas, Despoina Chatzakou, Ilias
Leontiadis, Jeremy Blackburn, Gianluca Stringhini, Athena Vakali, Michael
Sirivianos, and Nicolas Kourtellis. "Large scale crowdsourcing and
characterization of twitter abusive behavior." In Proceedings of the
International AAAI Conference on Web and Social Media, 2018.
Participation:
The data challenge is open to everyone.
Details about evaluation metrics and other aspects of the tasks can be
found at the website: <https://sigir-ecom.github.io/data-task.html>
https://sites.google.com/view/icwsm2020datachallenge/home
Submission instructions:
Submission should be made via EasyChair and must follow the formatting
guidelines for ICWSM-2020. All submissions must be anonymous and conform to
AAAI standards for double-blind review. Both short papers (4 pages
including references) and posters (2 pages including references) that
adhere to the 2-column AAAI format will be considered for review.
Submission Site: https://easychair.org/conferences/?conf=icwsm2020dc
Workshop URL: https://sites.google.com/view/icwsm2020datachallenge/home
Important Dates:
-
Data Challenge opens: Feb 21st, 2020
-
Paper Submission deadline - May 15th, 2020
-
Data Challenge notification - May 25th, 2020
-
ICWSM Data Challenge Full day Workshop - June 8th, 2020
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