Sainju Karla Dhungana, Kuffour Akosua, Young Lisa, Mishra Niti
Faculty of Social Science and Humanities, Ontario Tech University, 2000 Simcoe St N, Oshawa, ON L1G 0C5 Canada.
Rotman School of Management, University of Toronto, 105 St George St, Toronto, ON M5S 3E6 Canada.
Int J Bullying Prev. 2022;4(1):6-22. doi: 10.1007/s42380-021-00098-3. Epub 2021 Jun 7.
Bullying literature notes that aside from the dyadic relationship of target and perpetrator, there are other participant roles in the bullying process including those that reinforce the perpetrator and those that stand up for the target. Most examinations of bullying roles have relied on self-reported data, which suffer from key limitations such as response and recall bias. Twitter data provides a way to overcome these limitations and extend our current understanding of bullying roles. The current study provides one of the first qualitative examinations of tweets to analyze the disclosure and sharing of bullying-related online and offline episodes. Through a qualitative content analysis, the study examines 780 tweets to analyze the descriptions and characteristics of three participant roles: the perpetrator, target, and helper. The results provide multidimensional insights into the context and relationships between bullying roles. The results reveal that each of the bullying role players tweet to share varying perspectives and the discussions transcend beyond just online exchanges. The results also confirm that Twitter is used not only as a channel for bullying but also as a tool for connection between the different role players. Implications of how Twitter can be leveraged to promote anti-bullying initiatives to educate and inform users about bullying, while also helping build resilience and emotional regulation, are discussed. Additionally, the study also has implications for artificial intelligence and can help to build improved classifiers to detect bullying-related discourse and content online.
关于霸凌的文献指出,除了受害者与霸凌者的二元关系外,霸凌过程中还存在其他参与者角色,包括那些支持霸凌者的人和那些为受害者挺身而出的人。大多数对霸凌角色的研究都依赖于自我报告数据,这些数据存在诸如回应和回忆偏差等关键局限性。推特数据提供了一种克服这些局限性的方法,并扩展了我们目前对霸凌角色的理解。当前的研究首次对推文进行了定性分析,以分析与霸凌相关的线上和线下事件的披露与分享情况。通过定性内容分析,该研究考察了780条推文,以分析三种参与者角色(霸凌者、受害者和帮助者)的描述及特征。研究结果为霸凌角色之间的背景和关系提供了多维度的见解。结果显示,每个霸凌角色的参与者发推文是为了分享不同的观点,而且讨论不仅仅局限于线上交流。研究结果还证实,推特不仅被用作霸凌的渠道,也是不同角色参与者之间建立联系的工具。文中讨论了如何利用推特来推动反霸凌倡议,以便教育和告知用户有关霸凌的信息,同时还能帮助培养适应能力和情绪调节能力。此外,该研究对人工智能也有启示意义,有助于构建更完善的分类器来检测网上与霸凌相关的话语和内容。