@inproceedings{thapa-etal-2025-challenges,
title = "Challenges and Applications of Automated Extraction of Socio-political Events at the age of Large Language Models",
author = "Thapa, Surendrabikram and
Adhikari, Surabhi and
Tanev, Hristo and
Hurriyetoglu, Ali",
editor = {H{\"u}rriyeto{\u{g}}lu, Ali and
Tanev, Hristo and
Thapa, Surendrabikram},
booktitle = "Proceedings of the 8th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Texts",
month = sep,
year = "2025",
address = "Varna, Bulgaria",
publisher = "INCOMA Ltd., Shoumen, Bulgaria",
url = "https://aclanthology.org/2025.case-1.2/",
pages = "6--19",
abstract = "Socio-political event extraction (SPE) enables automated identification of critical events such as protests, conflicts, and policy shifts from unstructured text. As a foundational tool for journalism, social science research, and crisis response, SPE plays a key role in understanding complex global dynamics. The emergence of large language models (LLMs) like GPT-4 and LLaMA offers new opportunities for flexible, multilingual, and zero-shot SPE. However, applying LLMs to this domain introduces significant risks, including hallucinated outputs, lack of transparency, geopolitical bias, and potential misuse in surveillance or censorship. This position paper critically examines the promises and pitfalls of LLM-driven SPE, drawing on recent datasets and benchmarks. We argue that SPE is a high-stakes application requiring rigorous ethical scrutiny, interdisciplinary collaboration, and transparent design practices. We propose a research agenda focused on reproducibility, participatory development, and building systems that align with democratic values and the rights of affected communities."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="thapa-etal-2025-challenges">
<titleInfo>
<title>Challenges and Applications of Automated Extraction of Socio-political Events at the age of Large Language Models</title>
</titleInfo>
<name type="personal">
<namePart type="given">Surendrabikram</namePart>
<namePart type="family">Thapa</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Surabhi</namePart>
<namePart type="family">Adhikari</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Hristo</namePart>
<namePart type="family">Tanev</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ali</namePart>
<namePart type="family">Hurriyetoglu</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2025-09</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 8th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Texts</title>
</titleInfo>
<name type="personal">
<namePart type="given">Ali</namePart>
<namePart type="family">Hürriyetoğlu</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Hristo</namePart>
<namePart type="family">Tanev</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Surendrabikram</namePart>
<namePart type="family">Thapa</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>INCOMA Ltd., Shoumen, Bulgaria</publisher>
<place>
<placeTerm type="text">Varna, Bulgaria</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>Socio-political event extraction (SPE) enables automated identification of critical events such as protests, conflicts, and policy shifts from unstructured text. As a foundational tool for journalism, social science research, and crisis response, SPE plays a key role in understanding complex global dynamics. The emergence of large language models (LLMs) like GPT-4 and LLaMA offers new opportunities for flexible, multilingual, and zero-shot SPE. However, applying LLMs to this domain introduces significant risks, including hallucinated outputs, lack of transparency, geopolitical bias, and potential misuse in surveillance or censorship. This position paper critically examines the promises and pitfalls of LLM-driven SPE, drawing on recent datasets and benchmarks. We argue that SPE is a high-stakes application requiring rigorous ethical scrutiny, interdisciplinary collaboration, and transparent design practices. We propose a research agenda focused on reproducibility, participatory development, and building systems that align with democratic values and the rights of affected communities.</abstract>
<identifier type="citekey">thapa-etal-2025-challenges</identifier>
<location>
<url>https://aclanthology.org/2025.case-1.2/</url>
</location>
<part>
<date>2025-09</date>
<extent unit="page">
<start>6</start>
<end>19</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Challenges and Applications of Automated Extraction of Socio-political Events at the age of Large Language Models
%A Thapa, Surendrabikram
%A Adhikari, Surabhi
%A Tanev, Hristo
%A Hurriyetoglu, Ali
%Y Hürriyetoğlu, Ali
%Y Tanev, Hristo
%Y Thapa, Surendrabikram
%S Proceedings of the 8th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Texts
%D 2025
%8 September
%I INCOMA Ltd., Shoumen, Bulgaria
%C Varna, Bulgaria
%F thapa-etal-2025-challenges
%X Socio-political event extraction (SPE) enables automated identification of critical events such as protests, conflicts, and policy shifts from unstructured text. As a foundational tool for journalism, social science research, and crisis response, SPE plays a key role in understanding complex global dynamics. The emergence of large language models (LLMs) like GPT-4 and LLaMA offers new opportunities for flexible, multilingual, and zero-shot SPE. However, applying LLMs to this domain introduces significant risks, including hallucinated outputs, lack of transparency, geopolitical bias, and potential misuse in surveillance or censorship. This position paper critically examines the promises and pitfalls of LLM-driven SPE, drawing on recent datasets and benchmarks. We argue that SPE is a high-stakes application requiring rigorous ethical scrutiny, interdisciplinary collaboration, and transparent design practices. We propose a research agenda focused on reproducibility, participatory development, and building systems that align with democratic values and the rights of affected communities.
%U https://aclanthology.org/2025.case-1.2/
%P 6-19
Markdown (Informal)
[Challenges and Applications of Automated Extraction of Socio-political Events at the age of Large Language Models](https://aclanthology.org/2025.case-1.2/) (Thapa et al., CASE 2025)
ACL