News Deja Vu: Connecting Past and Present with Semantic Search
Brevin Franklin, Emily Silcock, Abhishek Arora, Tom Bryan, Melissa Dell
Abstract
Social scientists and the general public often analyze contemporary events by drawing parallels with the past, a process complicated by the vast, noisy, and unstructured nature of historical texts. For example, hundreds of millions of page scans from historical newspapers have been noisily transcribed. Traditional sparse methods for searching for relevant material in these vast corpora, e.g., with keywords, can be brittle given complex vocabularies and OCR noise. This study introduces News Deja Vu, a novel semantic search tool that leverages transformer large language models and a bi-encoder approach to identify historical news articles that are most similar to modern news queries. News Deja Vu first recognizes and masks entities, in order to focus on broader parallels rather than the specific named entities being discussed. Then, a contrastively trained, lightweight bi-encoder retrieves historical articles that are most similar semantically to a modern query, illustrating how phenomena that might seem unique to the present have varied historical precedents. Aimed at social scientists, the user-friendly News Deja Vu package is designed to be accessible for those who lack extensive familiarity with deep learning. It works with large text datasets, and we show how it can be deployed to a massive scale corpus of historical, open-source news articles. While human expertise remains important for drawing deeper insights, News Deja Vu provides a powerful tool for exploring parallels in how people have perceived past and present.- Anthology ID:
- 2024.nlpcss-1.8
- Volume:
- Proceedings of the Sixth Workshop on Natural Language Processing and Computational Social Science (NLP+CSS 2024)
- Month:
- June
- Year:
- 2024
- Address:
- Mexico City, Mexico
- Editors:
- Dallas Card, Anjalie Field, Dirk Hovy, Katherine Keith
- Venues:
- NLP+CSS | WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 99–112
- Language:
- URL:
- https://aclanthology.org/2024.nlpcss-1.8
- DOI:
- Cite (ACL):
- Brevin Franklin, Emily Silcock, Abhishek Arora, Tom Bryan, and Melissa Dell. 2024. News Deja Vu: Connecting Past and Present with Semantic Search. In Proceedings of the Sixth Workshop on Natural Language Processing and Computational Social Science (NLP+CSS 2024), pages 99–112, Mexico City, Mexico. Association for Computational Linguistics.
- Cite (Informal):
- News Deja Vu: Connecting Past and Present with Semantic Search (Franklin et al., NLP+CSS-WS 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-5/2024.nlpcss-1.8.pdf