检测LGBTQ+群体的网络欺凌实例
Detecting LGBTQ+ Instances of Cyberbullying
AI总结：
本文研究利用Transformer模型识别针对LGBTQ+群体的网络欺凌，分析不同模型在复杂微妙欺凌行为中的有效性。
摘要：
社交媒体持续影响人类发展轨迹，但其引入也使键盘成为武器，使原本用于现实欺凌的攻击性语言跃入屏幕，即网络欺凌。网络欺凌对全球青少年构成重大威胁，影响许多人心理健康。LGBTQ+群体尤其易受网络欺凌影响，研究发现认同LGBTQ+与遭受更多在线骚扰存在强相关性。因此，开发能准确识别LGBTQ+成员网络欺凌事件的机器学习模型至关重要。本研究旨在比较几种Transformer模型在识别针对LGBTQ+个体网络欺凌方面的有效性，通过真实社交媒体数据评估现有方法的优劣。
英文摘要：
Social media continues to have an impact on the trajectory of humanity. However, its introduction has also weaponized keyboards, allowing the abusive language normally reserved for in-person bullying to jump onto the screen, i.e., cyberbullying. Cyberbullying poses a significant threat to adolescents globally, affecting the mental health and well-being of many. A group that is particularly at risk is the LGBTQ+ community, as researchers have uncovered a strong correlation between identifying as LGBTQ+ and suffering from greater online harassment. Therefore, it is critical to develop machine learning models that can accurately discern cyberbullying incidents as they happen to LGBTQ+ members. The aim of this study is to compare the efficacy of several transformer models in identifying cyberbullying targeting LGBTQ+ individuals. We seek to determine the relative merits and demerits of these existing methods in addressing complex and subtle kinds of cyberbullying by assessing their effectiveness with real social media data.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
