About NSG 2024
Artificial intelligence (AI), specifically, Natural Language Processing (NLP) is being hailed as a new breeding ground for immense innovation potential. While scholars believe that NLP has enormous potential for excessive growth, one question remains: how can it be used for the better welfare of the society? Researchers believe that NLP-based technologies could help to solve societal issues such as equality and inclusion, education, health, and hunger, and climate action etc. and many more. The field is focused on delivering positive social impact in accordance with the priorities outlined in the United Nations’ 17 Sustainable Development Goals (SDGs). Tackling these questions requires a concerted, collaborative effort across all sectors of society. The Symposium on NLP for Social Good is a novel effort that aims to enable NLP researchers and scholars from interdisciplinary field who want to think about the societal implications of their work for solving humanitarian and environmental challenges. The symposium aims to support fundamental research and engineering efforts and empower the social sector with tools and resources, while collaborating with partners from all sectors to maximise effect in solving problems within public health, nature & society, climate & energy, accessibility, crisis response etc.
Call for Papers
NSG 2024 invites authors to submit papers on research that exploits different NLP techniques to address different social issues (e.g. education, law, healthcare, climate change or any priorities in SDG).
Topics of interest include but are not limited to:
- Applications and solutions on different topics corresponding to NLP for Social Good (NSG) theme.
- Natural Language Interfaces and Interaction: design and implementation of Natural Language Interfaces, user studies with human participants on issues related to NSG topics.
- Large Language Models & Vision Language Models: Opportunities and Risks of using LLMs and VLMs in NSG.
- eXplainable Artificial Intelligence (XAI): Scope of Interpretability in NSG topics.
- Corpus/Dataset Analysis: Corpus or dataset collection or analysis for NSG related topics
- Multi-modal solutions to the theme of NSG.
- Unique proposition and contribution in any 17 goals of SDG using NLP.
Authors should follow the CEUR single-column conference format and submit their manuscripts in pdf via Easychair conference page (submissions are NOW OPEN). Submissions must be 2 to 8 pages of content (plus any number of additional pages for reference).The review process is double-blind. All questions about submissions should be emailed to firstname.lastname@example.org
- Paper submission deadline: 15th March, 2024
- Paper notification: 12th April, 2024
- Camera-ready deadline: 16th April, 2024
- NSG 2024: 25th-26th April, 2024
- Manfred Stede (Keynote Talk)
Bio: Manfred Stede is a Professor of applied computational linguistics at Potsdam University, Germany. His research and teaching activities revolve around issues in discourse structure and automatic discourse parsing, inlcuding applications in sentiment analysis and argument mining. For several years now, he actively collaborates with social scientists from different disciplines (political science, education science, communication science) on research questions involving political argumentation, social media analysis, and a focus on discourses about climate change. Stede is a (co-) author of four books, 30 journal papers, and 150 conference or workshop papers and book chapters.Title: NLP on Climate Change Discourse: Two Case Studies
Abstract: The debate around climate change (CC) — its extent, its causes, and the necessary responses — is intense and of global importance. The ongoing discourses are a prominent object of study in several Social Sciences, while in the natural language processing community, this domain has so far received relatively little attention. In my talk, I first give a brief overview of types of approaches and data, and then report on two case studies that we are currently conducting in my research group. The first tackles the notion of "framing" (the perspective taken in viewing an issue) in CC-related editorials of the journals 'Nature' and 'Science': We proceed from a coarse-grained text-level labeling to increasingly detailed clause-level annotation of framing CC, and run experiments on automatic classification. The second involves a corpus of parliamentary speeches, press releases and tweets from the members of the German parliament (2017-2021) and compares their ways of addressing CC, contrasting on the one hand the different communication channels and on the other hand the party affiliations of the speakers.
- Sophia Ananiadou (Keynote Talk)
To be Announced
This will be a hybrid event. Registered participants will also be sent zoom links.
Previous Events: NSG 2023
Please reach out to the organizers for any questions via this email: email@example.com