Work

Exploring the effective nodes of interventions for cyberbullying victimization and anxiety symptoms: A simulation-based network analysis

Year: 2024

Type: conference-paper

Abstract: This research explores the connection between adolescent cyberbullying victimization and anxiety based purely on the application of two techniques, namely, the NodeIdentifyR algorithm and the Ising model. The analysis carried out with the Ising model reveals the central symptom to be Upset Jokes (CBV4) in the network. The NodeIdentifyR algorithm, therefore, produces two divergent pathways for treatment and prevention intervention. The focus of treatment should, however, primarily be in the reduction of anxiety symptoms, particularly Trouble Relaxing (ANX4) and Afraid (ANX7). For prevention-oriented interventions, some issues might be more effectively addressed in targeting CBV, especially Tease Fun (CBV2) and Upset Jokes (CBV4). This research shows that educational data mining enables the effective implementation of educational strategies. Thus, such applications enhance intervention effectiveness. This highlights the critical role played by IT-the improvement of quality and educational services by the promotion of students' well-being interventions via data.

Source: International Conference on Information Education and Artificial Intelligence (ICIEAI)

DOI: 10.1145/3724504.3724628

Authors: Fang Li, Yuan Fang, Zhiyan Chen

Institutions: Chinese Academy of Sciences, Institute of Psychology, Chinese Academy of Sciences, University of Chinese Academy of Sciences

Language: English

Topic: Bullying, Victimization, and Aggression

Subfield: Social Psychology

Field: Psychology

Domain: Social Sciences

SDG: Good health and well-being

Open Access status: hybrid

OpenAlex ID: W4410210393

FWCI: 0.71

Cites: 10

Cited by: 1

Related to: 10