Papers with online communities

5 papers
Analyzing Norm Violations in Live-Stream Chat (2023.emnlp-main)

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Challenge: Existing methods for detecting toxic language and norm violations are limited to live-streaming platforms . existing methods are less effective when applied to live streaming platforms based on a limited time frame .
Approach: They propose to use contextual information to automatically moderate toxic content on live streaming platforms.
Outcome: The proposed model improves on live-streaming platforms by 35%.
Multi-Agent Comedy Club: Investigating Community Discussion Effects on LLM Humor Generation (2026.findings-acl)

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Challenge: Existing studies on the use of multi-turn interaction and feedback for LLM writing focus on prompts and localized feedback.
Approach: They build a controlled multi-agent sandbox that instantiates a small standup comedy community and allows it to manipu-late whether public reception is generated, logged, and fed back into later rounds.
Outcome: The proposed model improves craft/clarity and social response with occasional increases in aggressive humor.
Short-Term Meaning Shift: A Distributional Exploration (N19-1)

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Challenge: a new study examines the phenomenon of short-term meaning shift in online communities . the authors use distributional representations to explore the phenomenon .
Approach: They propose to use distributional representations to explore short-term meaning shift in online communities.
Outcome: The proposed model has problems distinguishing meaning shift from referential phenomena, and measures contextual variability to remedy this.
Where Do People Tell Stories Online? Story Detection Across Online Communities (2024.acl-long)

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Challenge: Story detection in online communities is a challenging task as stories are scattered across communities and interwoven with non-storytelling spans within a single text.
Approach: They propose a toolkit to detect stories in online communities using an annotated reddit dataset and a codebook adapted to social media context.
Outcome: The proposed toolkit includes an annotation-rich dataset of 502 Reddit posts and comments . it also includes a codebook adapted to the social media context and models to predict storytelling at document and span levels.
Offensive Language Identification in Greek (2020.lrec-1)

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Challenge: a gap in the literature on offensive language has been addressed with studies on Spanish, Hindi, and German.
Approach: They present a Greek annotated dataset for offensive language identification . it contains 4,779 tweets annotating offensive and not offensive posts from Twitter . they evaluate several computational models trained and tested on the dataset .
Outcome: The proposed dataset contains 4,779 tweets annotated as offensive and not offensive . the authors show that the proposed dataset is similar to the OLID dataset for English .

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