| 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 |
| 1. What are the respective challenges of working with global or local news sources in automated information extraction? | |
| 2. How should news articles in local sources that are about countries other than the focus country should be treated?[1] | |
| 3. How can we address possible problems of editorial bias and/or censorship in source selection? | |
| 10:30 - 11:00 | Coffee break |
| 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 |
| 1. How should texts containing information about multiple real world protest events be handled in event information extraction? | |
| 2. How can multiple real world events in single new articles be separated? | |
| 3. What are the challenges of event co-referencing? | |
| 4. What are the benefits of event deduplication? | |
| 5. Is event deduplication really worth it? | |
| 6. If deduplication is necessary, how can this be achieved cost-efficiently with minimum data loss? | |
| 12:30 - 14:00 | Lunch |
| 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 |
| 14:40 - 15:30 | DISCUSSION - Generalizability |
| 1. How does variation in source language effect recall and precision performance of automated tools? | |
| 2. How would automated translation of source material effect classification and extraction performance? | |
| 3. How can automated translation of source material be optimized in terms of costs and performance? | |
| 4. What are the challenges of coming up with event ontologies that would accommodate variations in contentious politics over time and across country contexts? | |
| 5. What are the challenges of dealing with various editorial styles and/or web content formats (i.e. in tokenization) in text extraction? | |
| 6. What kind of automated text processing tools would best suit unsupervised domain adaptation? | |
| 15:30 - 16:00 | Coffee break |
| 16:00 - 16:30 | Discussion - Ethics |
| 1. What ethical concerns would automated information extraction from protest event news raise? | |
| 2. What are the ethical responsibilities of researchers working on automated protest event data extraction towards social groups and individuals engaging in protest? | |
| 3. How could we address and resolve possible ethical issue raised by automated information extraction from protest event news? | |
| 16:30 - 17:30 | Discussion - Prospects |
| How can we organize publication of the workshop proceedings? Some options are CEUR, a special issue in a journal, etc. | |
| What issue can we address together in order to advance state-of-the-art for automated protest event information collection? | |
| 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 | |
| Are there any venues we can write proposals for funding or resources? | |