An official website of the United States government
Cyberbullying has become a prominent risk for youth and an increasing concern for parents. To help parents reduce their child’s cyberbullying risk, anti-bullying apps (ABAs)—mobile applications for identifying and preventing instances of cyberbullying—have been developed in recent years. Given that ABAs are an emerging technology, limited research has been conducted to understand the factors predicting parents’ intentions to use them. Drawing on three interdisciplinary theoretical frameworks, a sample of parents in the U.S. recruited through Amazon Mechanical Turk completed an online survey to assess parents’ knowledge of, attitudes about, and intentions to use ABAs. Participants also rated the importance of a range of ABA functions and provided information about their child’s social media use and bullying history. A series of path analyses revealed that the importance parents placed on an app’s ability to provide information about their child’s cyberbullying risk predicted more positive attitudes toward ABAs and greater perceived usefulness of them. Stronger intentions to use ABAs were predicted by greater cyberbullying concern, greater importance of social recommendations, greater perceived usefulness, more positive attitudes toward the apps, and lower ratings of the importance of ease of use. These findings shed light on the factors predicting parents’ intentions to use ABAs and the app features they view as most important. Crucial directions for future research and implications for antibullying efforts are discussed.
more »
« less
ActionPoint: An App to Combat Cyberbullying by Strengthening Parent-Teen Relationships
Due to the increased prevalence of cyberbullying and the detrimental impact it can have on adolescents, there is a critical need for tools to help combat cyberbullying. This paper introduces the ActionPoint app, a mobile application based on empirical work highlighting the importance of strong parent-teen relationships for reducing cyberbullying risk. The app is designed to help families improve their communication skills, set healthy boundaries for social media use, identify instances of cyberbullying and cyberbullying risk, and, ultimately, decrease the negative outcomes associated with cyberbullying. The app guides parents and teens through a series of interactive modules that engage them in evidence-based activities that promote better understanding of cyberbullying risks and healthy online behaviors. In this paper, we describe the app design, the psychology research supporting the design of each module, the architecture and implementation details, and crucial paths to extend the app.
more »
« less
- PAR ID:
- 10572821
- Publisher / Repository:
- IEEE
- Date Published:
- ISBN:
- 979-8-3503-2914-8
- Page Range / eLocation ID:
- 99 to 103
- Subject(s) / Keyword(s):
- cyberbullying anti-bullying tools social networks social media parents teens mobile applications
- Format(s):
- Medium: X
- Location:
- Herndon, VA, USA
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Social media platforms and online gaming sites play a pervasive role in facilitating peer interaction and social development for adolescents, but they also pose potential threats to health and safety. It is crucial to tackle cyberbullying issues within these platforms to ensure the healthy social development of adolescents. Cyberbullying has been linked to adverse mental health outcomes among adolescents, including anxiety, depression, academic underperformance, and an increased risk of suicide. While cyberbullying is a concern for all adolescents, those with disabilities are particularly susceptible and face a higher risk of being targets of cyberbullying. Our research addresses these challenges by introducing a personalized online virtual companion guided by artificial intelligence (AI). The web-based virtual companion’s interactions aim to assist adolescents in detecting cyberbullying. More specifically, an adolescent with ASD watches a cyberbullying scenario in a virtual environment, and the AI virtual companion then asks the adolescent if he/she detected cyberbullying. To inform the virtual companion in real time to know if the adolescent has learned about detecting cyberbullying, we have implemented fast and lightweight cyberbullying detection models employing the T5-small and MobileBERT networks. Our experimental results show that we obtain comparable results to the state-of-the-art methods despite having a compact architecture.more » « less
-
Cyberbullying has become increasingly prevalent, particularly on social media. There has also been a steady rise in cyberbullying research across a range of disciplines. Much of the empirical work from computer science has focused on developing machine learning models for cyberbullying detection. Whereas machine learning cyberbullying detection models can be improved by drawing on psychological theories and perspectives, there is also tremendous potential for machine learning models to contribute to a better understanding of psychological aspects of cyberbullying. In this paper, we discuss how machine learning models can yield novel insights about the nature and defining characteristics of cyberbullying and how machine learning approaches can be applied to help clinicians, families, and communities reduce cyberbullying. Specifically, we discuss the potential for machine learning models to shed light on the repetitive nature of cyberbullying, the imbalance of power between cyberbullies and their victims, and causal mechanisms that give rise to cyberbullying. We orient our discussion on emerging and future research directions, as well as the practical implications of machine learning cyberbullying detection models.more » « less
-
Foregrounding Women's Safety in Mobile Social Matching and Dating Apps: A Participatory Design StudyThe design of social matching and dating apps has changed continually through the years, marked notably by a shift to mobile devices, and yet user safety has not historically been a driver of design despite mounting evidence of sexual and other harms. This paper presents a participatory design study with women-a demographic at disproportionate risk of harm through app-use-about how mobile social matching apps could be designed to foreground their safety. Findings indicate that participants want social matching apps to augment women's abilities for self-protection, reflected in three new app roles: 1) the cloaking device, through which the social matching app helps women dynamically manage visibility to geographically nearby users, 2) the informant, through which the app helps women predict risk of harm associated with a recommended social opportunity, and 3) the guardian, through which the app monitors a user's safety during face-to-face meetings and augments their response to risk.more » « less
-
Cyberbullying is a growing problem across social media platforms, inflicting short and long-lasting effects on victims. To mitigate this problem, research has looked into building automated systems, powered by machine learning, to detect cyberbullying incidents, or the involved actors like victims and perpetrators. In the past, systematic reviews have examined the approaches within this growing body of work, but with a focus on the computational aspects of the technical innovation, feature engineering, or performance optimization, without centering around the roles, beliefs, desires, or expectations of humans. In this paper, we present a human-centered systematic literature review of the past 10 years of research on automated cyberbullying detection. We analyzed 56 papers based on a three-prong human-centeredness algorithm design framework - spanning theoretical, participatory, and speculative design. We found that the past literature fell short of incorporating human-centeredness across multiple aspects, ranging from defining cyberbullying, establishing the ground truth in data annotation, evaluating the performance of the detection models, to speculating the usage and users of the models, including potential harms and negative consequences. Given the sensitivities of the cyberbullying experience and the deep ramifications cyberbullying incidents bear on the involved actors, we discuss takeaways on how incorporating human-centeredness in future research can aid with developing detection systems that are more practical, useful, and tuned to the diverse needs and contexts of the stakeholders.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/WFPST58552.2024.00008
