Towards Effective Counter-Responses: Aligning Human Preferences with Strategies to Combat Online Trolling (2024.findings-emnlp)
Copied to clipboard
| Challenge: | Existing methods to counter trolling in online communities are not yet available to address the diversity of trolling behaviors. |
| Approach: | They propose a method for generating counter-responses to trolls by aligning these strategies with human preferences across different trolled contexts. |
| Outcome: | The proposed approach reduces negative effects of trolling and improves the online community environment. |
Similar Papers
ELF22: A Context-based Counter Trolling Dataset to Combat Internet Trolls (2022.lrec-1)
Copied to clipboard
| Challenge: | a new dataset aims to automate the method to counter trolls . trolleds cause psychological damage to individuals and increase social costs . |
| Approach: | They propose to use a dataset to generate counter responses by varying counter responses according to a given strategy. |
| Outcome: | The proposed method improves strategy-controlled sentence generation. |
Modeling Trolling in Social Media Conversations (L18-1)
Copied to clipboard
| Challenge: | a new classification of trolling allows for comment-based analysis from both the trolls' and the responders' perspectives . a trolled's intentions may cause a negative psychological impact on the participants . |
| Approach: | They propose a trolling categorization that allows comment-based analysis from both trolls' and responders' perspectives . they annotate and release a dataset containing excerpts of Reddit conversations involving suspected trolled users . |
| Outcome: | The proposed model allows comment-based analysis from both the trolls' and the responders' perspectives. |
Generating Counter Narratives against Online Hate Speech: Data and Strategies (2020.acl-main)
Copied to clipboard
| Challenge: | Hate Speech (HS) is a pervasive issue that spreads quickly and widely . research has focused on avoiding undesired effects that come with content moderation . |
| Approach: | They propose to use large scale unsupervised language models to generate responses to hate effectively using large scale models. |
| Outcome: | The proposed methods lack quality data and produce generic/repetitive responses. |
Countering Hateful and Offensive Speech Online - Open Challenges (2024.emnlp-tutorials)
Copied to clipboard
Leon Derczynski, Marco Guerini, Debora Nozza, Flor Miriam Plaza-del-Arco, Jeffrey Sorensen, Marcos Zampieri
| Challenge: | a comprehensive understanding of the field is needed to maintain respectful and inclusive online environments. |
| Approach: | This tutorial aims to provide attendees with a comprehensive understanding of the field by delving into essential dimensions such as multilingualism, counter-narrative generation, a hands-on session with one of the most popular APIs for detecting hate speech, fairness, and ethics in AI, and the use of recent advanced approaches. |
| Outcome: | This tutorial aims to provide attendees with a comprehensive understanding of the field by delving into essential dimensions such as multilingualism, counter-narrative generation, a hands-on session with one of the most popular APIs for detecting hate speech, fairness, and ethics in AI, and the use of recent advanced approaches. |
NLP for Counterspeech against Hate: A Survey and How-To Guide (2024.findings-naacl)
Copied to clipboard
| Challenge: | Recent studies have focused on the challenges of analysing, collecting, classifying, and automatically generating counterspeech, to reduce the huge burden of manually producing it. |
| Approach: | They propose a guide for doing research on counterspeech, with detailed examples and best practices that can be learnt from the NLP community. |
| Outcome: | The proposed strategies can reduce online and offline violence while preserving the freedom of speech of the users. |
LLM generated responses to mitigate the impact of hate speech (2024.findings-emnlp)
Copied to clipboard
Jakub Podolak, Szymon Łukasik, Paweł Balawender, Jan Ossowski, Jan Piotrowski, Katarzyna Bakowicz, Piotr Sankowski
| Challenge: | a study aims to determine the effectiveness of large language models to counteract hate speech . it is the first real-life A/B test evaluating the effectiveness . |
| Approach: | They conduct the first real-life A/B test assessing the effectiveness of LLM-generated counter-speech. |
| Outcome: | The proposed system reduces user engagement by over 20%, the study shows . the proposed metric is based on a simple metric and is scalable to other platforms . |
Detecting Community Sensitive Norm Violations in Online Conversations (2021.findings-emnlp)
Copied to clipboard
Chan Young Park, Julia Mendelsohn, Karthik Radhakrishnan, Kinjal Jain, Tushar Kanakagiri, David Jurgens, Yulia Tsvetkov
| Challenge: | Existing efforts to identify unacceptable behavior have focused on toxicity as the sole form of community norm violation. |
| Approach: | They propose a dataset that focuses on a more complete spectrum of community norms and their violations in local conversational and global contexts. |
| Outcome: | The proposed model improves the detection of community norm violations in local conversational and global contexts. |
A Just and Comprehensive Strategy for Using NLP to Address Online Abuse (P19-1)
Copied to clipboard
| Challenge: | Current methods to detect online abuse focus on a narrow definition of abuse to detriment of victims seeking validation and solutions. |
| Approach: | They argue that the NLP community needs to make three substantive changes to tackle both more subtle and more serious forms of abuse. |
| Outcome: | The proposed approach would address the problem of abuse in a more inclusive and productive way. |
On the Effectiveness of Adversarial Robustness for Abuse Mitigation with Counterspeech (2024.naacl-long)
Copied to clipboard
| Challenge: | Recent work on automated counterspeech systems focused on synthetic data but rarely looked into how the public deals with abuse. |
| Approach: | They propose to curate a new dataset of abuse and replies from footballers for study of public figure abuse and use it to examine how models can handle adversarial attacks. |
| Outcome: | The proposed model is robust against adversarial attacks across domains and can handle abuse in the real world. |
Integrating Argumentation and Hate-Speech-based Techniques for Countering Misinformation (2024.emnlp-main)
Copied to clipboard
| Challenge: | scalable strategies to combat online misinformation are short-term and insufficient, authors say . current reactive approaches, like content flagging and banning, do little to change perception of misinformants . human evaluations show that our framework generates expert-like responses . |
| Approach: | They propose a framework that generates persuasive responses from hate-speech counter-responses . human evaluations show that the framework generates expert-like responses . |
| Outcome: | The proposed framework generates expert-like responses and is 14% more engaging, 21% more natural, and 18% more factual than the best available alternatives. |