@inproceedings{dong-etal-2025-parallel,
title = "Parallel Communities Across the Surface Web and the Dark Web",
author = "Dong, Wenchao and
Sundriyal, Megha and
Park, Seongchan and
Kim, Jaehong and
Cha, Meeyoung and
Chakraborty, Tanmoy and
Lee, Wonjae",
editor = "Christodoulopoulos, Christos and
Chakraborty, Tanmoy and
Rose, Carolyn and
Peng, Violet",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2025",
month = nov,
year = "2025",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.findings-emnlp.987/",
pages = "18199--18218",
ISBN = "979-8-89176-335-7",
abstract = "Humans have an inherent need for community belongingness. This paper investigates this fundamental social motivation by compiling a large collection of parallel datasets comprising over 7 million posts and comments from Reddit and 200,000 posts and comments from Dread, a dark web discussion forum, covering similar topics. Grounded in five theoretical aspects of the Sense of Community framework, our analysis indicates that users on Dread exhibit a stronger sense of community membership. Our data analysis reveals striking similarities in post content across both platforms, despite the dark web{'}s restricted accessibility. However, these communities differ significantly in community-level closeness, including member interactions and greeting patterns that influence user retention and dynamics. We publicly release the parallel community datasets for other researchers to examine key differences and explore potential directions for further study."
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%0 Conference Proceedings
%T Parallel Communities Across the Surface Web and the Dark Web
%A Dong, Wenchao
%A Sundriyal, Megha
%A Park, Seongchan
%A Kim, Jaehong
%A Cha, Meeyoung
%A Chakraborty, Tanmoy
%A Lee, Wonjae
%Y Christodoulopoulos, Christos
%Y Chakraborty, Tanmoy
%Y Rose, Carolyn
%Y Peng, Violet
%S Findings of the Association for Computational Linguistics: EMNLP 2025
%D 2025
%8 November
%I Association for Computational Linguistics
%C Suzhou, China
%@ 979-8-89176-335-7
%F dong-etal-2025-parallel
%X Humans have an inherent need for community belongingness. This paper investigates this fundamental social motivation by compiling a large collection of parallel datasets comprising over 7 million posts and comments from Reddit and 200,000 posts and comments from Dread, a dark web discussion forum, covering similar topics. Grounded in five theoretical aspects of the Sense of Community framework, our analysis indicates that users on Dread exhibit a stronger sense of community membership. Our data analysis reveals striking similarities in post content across both platforms, despite the dark web’s restricted accessibility. However, these communities differ significantly in community-level closeness, including member interactions and greeting patterns that influence user retention and dynamics. We publicly release the parallel community datasets for other researchers to examine key differences and explore potential directions for further study.
%U https://aclanthology.org/2025.findings-emnlp.987/
%P 18199-18218
Markdown (Informal)
[Parallel Communities Across the Surface Web and the Dark Web](https://aclanthology.org/2025.findings-emnlp.987/) (Dong et al., Findings 2025)
ACL
- Wenchao Dong, Megha Sundriyal, Seongchan Park, Jaehong Kim, Meeyoung Cha, Tanmoy Chakraborty, and Wonjae Lee. 2025. Parallel Communities Across the Surface Web and the Dark Web. In Findings of the Association for Computational Linguistics: EMNLP 2025, pages 18199–18218, Suzhou, China. Association for Computational Linguistics.