This seminar will be webstreamed, in case you wish to attend the seminar through Webex, please send us an email to JRC-CAS-CSS4P@ec.europa.eu and we will share the connection details.
The webstreaming link will be available when the event starts.
- social sciences | data science | natural language processing | big data
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- Online only
- Live streaming available
Practical information
- When
- -
- Where
- Online only
- Livestream
- Starts on Wednesday 5 July 2023, 15:00 CEST
- Languages
- English
- Organisers
- Joint Research Centre
- Part of
Description
Language is the medium for many political activities, from campaigns to news reports. Natural language processing (NLP) uses computational tools to parse text into key information that is needed for policymaking. Common methods of NLP include text classification, topic modelling, event extraction, and text scaling which can be used for policymaking through four major applications including data collection for evidence-based policymaking, interpretation of political decisions, policy communication, and investigation of policy effects. In her talk, Zhijing Jin, will present her latest CSS for Policy research update from the NLP perspective through an overview of applied studies such as (a) NLP to mine the causality behind policy trends, (b) NLP to check censorship patterns across countries, and (c) querying ChatGPT and GPT-4 about the causes behind social and political events.
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About the speaker

Zhijing Jin (she/her) is a Ph.D. at Max Planck Institute & ETH. Her research focuses on socially responsible NLP via causal and moral principles. Specifically, she works on expanding the impact of NLP by promoting NLP for social good, and developing CausalNLP to improve robustness, fairness, and interpretability of NLP models, as well as analyze the causes of social problems. She is co-supervised by Prof Bernhard Schoelkopf at Max Planck Institute (main supervisor), Prof Rada Mihalcea at University of Michigan (as a mentor), and Prof Mrinmaya Sachan and Prof Ryan Cotterell (co-supervisors through ELLIS program) at ETH Zürich. She has published at many NLP and AI venues (e.g., ACL, EMNLP, NAACL, COLING, NeurIPS, AAAI, AISTATS). Her work has been cited in MIT News, ACM TechNews, WeVolver, VentureBeat, and Synced. She is actively involved in AI for social good, as the organizer of NLP for Positive Impact Workshops at ACL 2021 and EMNLP 2022, and RobustML workshop at ICLR 2021. To support the NLP research community, she organizes the ACL Year-Round Mentorship Program. To foster the causality research community, she organized the Tutorial on CausalNLP at EMNLP 2022, and served as the Publications Chair for the 1st conference on Causal Learning and Reasoning (CLeaR). More information can be checked on her personal website: zhijing-jin.com
Contacts
General contact
- Name
- The CSS4P Team
- Postal address
- Via E. Fermi 2749, 21027 Ispra VA, Italy
- Office
- 46I - 00/014
- Social media