TextEssence: A Tool for Interactive Analysis of Semantic Shifts Between Corpora
Denis Newman-Griffis, Venkatesh Sivaraman, Adam Perer, Eric Fosler-Lussier, Harry Hochheiser
Abstract
Embeddings of words and concepts capture syntactic and semantic regularities of language; however, they have seen limited use as tools to study characteristics of different corpora and how they relate to one another. We introduce TextEssence, an interactive system designed to enable comparative analysis of corpora using embeddings. TextEssence includes visual, neighbor-based, and similarity-based modes of embedding analysis in a lightweight, web-based interface. We further propose a new measure of embedding confidence based on nearest neighborhood overlap, to assist in identifying high-quality embeddings for corpus analysis. A case study on COVID-19 scientific literature illustrates the utility of the system. TextEssence can be found at https://textessence.github.io.
BibTeX
@inproceedings{newman-griffis-etal-2021-textessence,
title = "{T}ext{E}ssence: A Tool for Interactive Analysis of Semantic Shifts Between Corpora",
author = "Newman-Griffis, Denis and
Sivaraman, Venkatesh and
Perer, Adam and
Fosler-Lussier, Eric and
Hochheiser, Harry",
editor = "Sil, Avi and
Lin, Xi Victoria",
booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demonstrations",
month = jun,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.naacl-demos.13/",
doi = "10.18653/v1/2021.naacl-demos.13",
pages = "106--115"
}