Categories |
DATA
|
About |
ICWSM 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:
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. Submission Site: https://easychair.org/conferences/?conf=icwsm2020dc Important Dates:
|
Call for Papers |
TASK DESCRIPTIONTask 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 80k 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://dataverse.mpi-sws.org/dataset.xhtml?persistentId=doi:10.5072/FK2/ZDTEMN 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. EVALUATIONDetails about evaluation metrics and other aspects of the tasks will be released soon. PARTICIPATIONThe data challenge is open to everyone. Please note that accepted submissions will require at least one registration for the conference. SUBMISSION INSTRUCTIONSSubmission 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 |
Summary |
ICWSM-DC 2020 : Data Challenge: Safety will take place in Atlanta, USA. It’s a 1 day event starting on Jun 08, 2020 (Monday) and will be winded up on Jun 08, 2020 (Monday). ICWSM-DC 2020 falls under the following areas: DATA, etc. Submissions for this Workshop can be made by Apr 25, 2020. Authors can expect the result of submission by May 01, 2020. Please check the official event website for possible changes before you make any travelling arrangements. Generally, events are strict with their deadlines. It is advisable to check the official website for all the deadlines. Other Details of the ICWSM-DC 2020
|
Credits and Sources |
[1] ICWSM-DC 2020 : Data Challenge: Safety |