Enabling Cross-Platform Comparison of Online Communities Using Content and Opinion Similarity
College of Information and Computer Science, University of Massachusetts at Amherst · MIT Lincoln Laboratory, Massachusetts Institute of Technology · University of Massachusetts Amherst and College of Information and Computer Science, University of Massachusetts at Amherst
PDF 由论文原始站点提供,PaperCompass 不保存论文文件。DOI 10.18653/v1/2024.findings-emnlp.586 ↗
摘要
With the continuous growth of online communities, understanding their similarities and dissimilarities is more crucial than ever for enhancing digital interactions, maintaining healthy interactions, and improving content recommendation and moderation systems. In this work, we present two novel techniques: BOTS for finding similarity between online communities based on their opinion, and Emb-PSR for finding similarity in the content they post. To facilitate finding the similarity based on opinion, we model the opinions on online communities using upvotes and downvotes as an indicator for community approval. Our results demonstrate that BOTS and Emb-PSR outperform existing techniques at their individual tasks while also being flexible enough to allow for cross-platform comparison of online communities. We demonstrate this novel cross-platform capability by comparing GAB with various subreddits.