09:00 -
10:30 |
PROJECT OVERVIEWS & Methods |
09:00 - 09:20 |
Introduction to Global
Contentious Politics (GLOCON) Project |
09:20 - 09:40 |
Roger Bock and Elizabeth
Boschee, Combining Machine Learning and Linguistic Intuition for Automatic
Coding of Protest Events |
09:40 - 10:00 |
Parang Saraf and Naren
Ramakrishnan, A Semi-Automated Approach for Extracting Political Events from
News Articles with High Recall Across Multiple Languages |
10:00 - 10:30 |
Discussion - Source Selection |
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1. What are the respective challenges of working with global
or local news sources in automated information extraction? |
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2. How should news articles in local sources that are about
countries other than the focus country should be treated?[1] |
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3. How can we address possible problems of editorial bias
and/or censorship in source selection? |
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10:30 - 11:00 |
Coffee break |
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11:00 - 12:30 |
DATA CHALLENGE |
11:00 - 11:20 |
Ali Hrriyetoğlu - Data
challenge overview: results of Ali Safaya |
11:20 - 11:40 |
Data challenge result 1: Anais
Ollagnier and Hywel Williams, Using Neuronal Network Embeddings for
Classification and Event Identification |
11:40 - 12:00 |
Data challenge result 2: Hristo
Tanev, Vanni Zavarella, Martin Atkinson and Jakub Piskorski, THE NEXUS EVENT
DETECTION SYSTEM AT COPE 2019 |
12:00 - 12:30 |
Discussion - Information
Extraction |
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1. How should texts containing information about multiple real
world protest events be handled in event information extraction? |
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2. How can multiple real world events in single new articles
be separated? |
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3. What are the challenges of event co-referencing? |
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4. What are the benefits of event deduplication? |
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5. Is event deduplication really worth it? |
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6. If deduplication is necessary, how can this be achieved
cost-efficiently with minimum data loss? |
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12:30 - 14:00 |
Lunch |
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14:00 - 15:30 |
EVALUATION |
14:00 - 14:20 |
Scott Althaus, Buddy Peyton and
Dan Shalmon, Validating Contentious Political Event Data with Aggregate and
Granular Comparisons: Methods and Application to Nigerias Conflict with Boko
Haram |
14:20 - 14:40 |
Fuyuki Kurasawa, Analyzing
Online Contention and Controversy: The Promises and Challenges of Deep
Learning |
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14:40 - 15:30 |
DISCUSSION - Generalizability |
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1. How does variation in source language effect recall and
precision performance of automated tools? |
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2. How would automated translation of source material effect
classification and extraction performance? |
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3. How can automated translation of source material be
optimized in terms of costs and performance? |
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4. What are the challenges of coming up with event ontologies
that would accommodate variations in contentious politics over time and
across country contexts? |
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5. What are the challenges of dealing with various editorial
styles and/or web content formats (i.e. in tokenization) in text extraction? |
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6. What kind of automated text processing tools would best
suit unsupervised domain adaptation? |
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15:30 - 16:00 |
Coffee break |
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16:00 - 16:30 |
Discussion - Ethics |
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1. What ethical concerns would automated information
extraction from protest event news raise? |
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2. What are the ethical responsibilities of researchers
working on automated protest event data extraction towards social groups and
individuals engaging in protest? |
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3. How could we address and resolve possible ethical issue
raised by automated information extraction from protest event news? |
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16:30 - 17:30 |
Discussion - Prospects |
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How can we organize publication
of the workshop proceedings? Some options are CEUR, a special issue in a
journal, etc. |
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What issue can we address
together in order to advance state-of-the-art for automated protest event
information collection? |
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What kind of collaborative
effort could be organized? Some options are: a) creating a dataset together,
e.g. annotating future vs. other events, creating a gold standard corpus of
contentious events database info, sharing language or computing resources |
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Are there any venues we can
write proposals for funding or resources? |
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