@inproceedings{abdelgaber-etal-2025-ai,
title = "{AI} Assistant for Socioeconomic Empowerment Using Federated Learning",
author = "Abdelgaber, Nahed and
Jahan, Labiba and
Castellano, Nino and
Oltmanns, Joshua and
Gupta, Mehak and
Zhang, Jia and
Pednekar, Akshay and
Basavaraju, Ashish and
Velazquez, Ian and
Ma, Zerui",
editor = {H{\"a}m{\"a}l{\"a}inen, Mika and
{\"O}hman, Emily and
Bizzoni, Yuri and
Miyagawa, So and
Alnajjar, Khalid},
booktitle = "Proceedings of the 5th International Conference on Natural Language Processing for Digital Humanities",
month = may,
year = "2025",
address = "Albuquerque, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.nlp4dh-1.42/",
doi = "10.18653/v1/2025.nlp4dh-1.42",
pages = "490--501",
ISBN = "979-8-89176-234-3",
abstract = "Socioeconomic status (SES) reflects an individual{'}s standing in society, from a holistic set of factors including income, education level, and occupation. Identifying individuals in low-SES groups is crucial to ensuring they receive necessary support. However, many individuals may be hesitant to disclose their SES directly. This study introduces a federated learning-powered framework capable of verifying individuals' SES levels through the analysis of their communications described in natural language. We propose to study language usage patterns among individuals from different SES groups using clustering and topic modeling techniques. An empirical study leveraging life narrative interviews demonstrates the effectiveness of our proposed approach."
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%0 Conference Proceedings
%T AI Assistant for Socioeconomic Empowerment Using Federated Learning
%A Abdelgaber, Nahed
%A Jahan, Labiba
%A Castellano, Nino
%A Oltmanns, Joshua
%A Gupta, Mehak
%A Zhang, Jia
%A Pednekar, Akshay
%A Basavaraju, Ashish
%A Velazquez, Ian
%A Ma, Zerui
%Y Hämäläinen, Mika
%Y Öhman, Emily
%Y Bizzoni, Yuri
%Y Miyagawa, So
%Y Alnajjar, Khalid
%S Proceedings of the 5th International Conference on Natural Language Processing for Digital Humanities
%D 2025
%8 May
%I Association for Computational Linguistics
%C Albuquerque, USA
%@ 979-8-89176-234-3
%F abdelgaber-etal-2025-ai
%X Socioeconomic status (SES) reflects an individual’s standing in society, from a holistic set of factors including income, education level, and occupation. Identifying individuals in low-SES groups is crucial to ensuring they receive necessary support. However, many individuals may be hesitant to disclose their SES directly. This study introduces a federated learning-powered framework capable of verifying individuals’ SES levels through the analysis of their communications described in natural language. We propose to study language usage patterns among individuals from different SES groups using clustering and topic modeling techniques. An empirical study leveraging life narrative interviews demonstrates the effectiveness of our proposed approach.
%R 10.18653/v1/2025.nlp4dh-1.42
%U https://aclanthology.org/2025.nlp4dh-1.42/
%U https://doi.org/10.18653/v1/2025.nlp4dh-1.42
%P 490-501
Markdown (Informal)
[AI Assistant for Socioeconomic Empowerment Using Federated Learning](https://aclanthology.org/2025.nlp4dh-1.42/) (Abdelgaber et al., NLP4DH 2025)
ACL
- Nahed Abdelgaber, Labiba Jahan, Nino Castellano, Joshua Oltmanns, Mehak Gupta, Jia Zhang, Akshay Pednekar, Ashish Basavaraju, Ian Velazquez, and Zerui Ma. 2025. AI Assistant for Socioeconomic Empowerment Using Federated Learning. In Proceedings of the 5th International Conference on Natural Language Processing for Digital Humanities, pages 490–501, Albuquerque, USA. Association for Computational Linguistics.