30.934, FYI: Call for Participation: CLEF ProtestNews 2019 Extracting Protests from New

[The LINGUIST List]

LINGUIST List: Vol-30-934. Wed Feb 27 2019. ISSN: 1069 - 4875.

Subject: 30.934, FYI: Call for Participation: CLEF ProtestNews 2019 Extracting Protests from New

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Date: Wed, 27 Feb 2019 13:41:25
From: Arda Akdemir [aakdemir at ku.edu.tr]
Subject: Call for Participation: CLEF ProtestNews 2019 Extracting Protests from New

 
Apologies for cross-posting & please share with anybody who may be interested
in this call. 

Call for Participation:
 
CLEF ProtestNews 2019
Extracting Protests from News Using Automated Methods

https://emw.ku.edu.tr/clef-protestnews-2019/
  
ProtestNews 2019 is a lab that is being organized as part of the Conference
and Labs of the Evaluation Forum 2019 (CLEF). The lab aims at extracting
protest event information from news articles across multiple countries using
machine learning (ML) and generalizable natural language processing (NLP).
This is a sub-task of our ERC-funded research, which aims to generate a
comparative protest databases for China, India, South Africa, Mexico and
Brazil (emw.ku.edu.tr). The lab aims at facilitating research in line of
improving generalizability of natural language processing systems. Our
objective is to develop text classification and information extraction tools
on one country and test them on data from different countries.
 
The results of our task will appear in the working notes proceedings,
published by CEUR Workshop Proceedings (CEUR-WS.org) and are presented in
the CLEF 2019. Time & Place:  09-12 September 2019, Lugano - Switzerland
         
We offer three subtasks and target research areas involve but not limited to:
 
- Information Retrieval
- Natural Language Processing
- Machine Learning, Deep Learning
- Big Data, Data Mining
 
with a focus on generalizability.
 
Tasks:

We split the ProtestNews task in three subtasks:

1) Task 1: News article classification as protest vs. non-protest is a binary
classification task that aims at discriminating between protest event related
news articles and any other news article. Task 1 forms the basis of the
subsequent tasks and is the first step towards extracting protest  event
related information from news articles.
2) Task 2: Event sentence detection aims at determining event sentences that
contain an event trigger or a mention of it. Event triggers refer to the
textual unit that makes a sentence to be annotated as an event sentence and an
event mention is any kind of mention to that event trigger. For example; ''In
the attack that happened yesterday 20 people were injured.'' and ''Today, we
received news that 2 people died in the hospital after the incident.'' would
be positive examples.
3) Task 3: Event information extraction is an event information extraction
task that targets mainly events. Information such as participants, time and
place of the event. So this task can be considered as a challenging Named
Entity Recognition task where the participants are expected to detect not only
the named entities found in the text but also be able to detect which ones are
related to event. F1 measure will be used to evaluate Task 3.
 
Subtasks two and three will be based on news articles that are labelled as
protest or not for subtask 1. Participants can choose to participate in one or
more of these subtasks independent of each other. The data from India will be
used for training and testing. Evaluations will be done using the dataset from
China.
 
Timeline:

Please register before April 26, 2019
(http://clef2019-labs-registration.dei.unipd.it/).
Data release: March 15, 2019.
Submission deadline is May 10, 2019.
 
 
Organizers:

Ali Hürriyetoglu: ahurriyetoglu at ku.edu.tr
Deniz Yüret: dyuret at ku.edu.tr
Erdem Yörük: eryoruk at ku.edu.tr
Çağrı Yoltar: cyoltar at ku.edu.tr
Burak Gürel: bgurel at ku.edu.tr
Fırat Duruşan: fdurusan at ku.edu.tr
Osman Mutlu: omutlu at ku.edu.tr
Arda Akdemir: aakdemir at ku.edu.tr
Theresa Gessler: Theresa.Gessler at eui.eu
Peter Makarov: makarov at cl.uzh.ch
 
Steering Committee:

Aline Villavicencio
Antal van den Bosch
Arzucan Özgür
Hristo Tanev
Kemal Oflazer
Sophia Ananiadou
 



Linguistic Field(s): Computational Linguistics





 



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