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title RedditEM: Unveiling Diachronic Semantic Shifts in Social Network Discourse
booktitle Proceedings of the 16th Asian Conference on Machine Learning
year 2025
volume 260
series Proceedings of Machine Learning Research
month 0
publisher PMLR
pdf https://raw.githubusercontent.com/mlresearch/v260/main/assets/zou25a/zou25a.pdf
url https://proceedings.mlr.press/v260/zou25a.html
openreview AlG4TinZB6
abstract Humans employ words to convey abstract concepts. The evolution of lexical semantics holds significance not only in Natural Language Processing applications but also in the realm of social computing research. However, the scarcity of diachronic word representations persists due to the substantial computational demands, particularly evident in the absence of large-scale and enduring diachronic word embeddings for social network texts. Herein, we introduce RedditEM, a comprehensive collection of diachronic word representations derived from Reddit English comment texts, featuring one word embedding per month spanning from January 2010 to December 2021. To assess the diachronic semantic shifts of words, we employ cosine distance metrics and juxtapose the embeddings’ neighborhoods. Our experimental findings underscore the utility of RedditEM in detecting alterations in word meanings within social networks and advancing social computing endeavors. Researchers interested in accessing this resource are cordially invited to contact us without hesitation.
layout inproceedings
issn 2640-3498
id zou25a
tex_title {RedditEM}: {U}nveiling Diachronic Semantic Shifts in Social Network Discourse
firstpage 968
lastpage 983
page 968-983
order 968
cycles false
bibtex_editor Nguyen, Vu and Lin, Hsuan-Tien
editor
given family
Vu
Nguyen
given family
Hsuan-Tien
Lin
bibtex_author Zou, Jiajun and Wu, Sixing and Yang, Jinshuai and Jiang, Minghu and Huang, Yongfeng
author
given family
Jiajun
Zou
given family
Sixing
Wu
given family
Jinshuai
Yang
given family
Minghu
Jiang
given family
Yongfeng
Huang
date 2025-01-14
address
container-title Proceedings of the 16th Asian Conference on Machine Learning
genre inproceedings
issued
date-parts
2025
1
14
extras