Takuro Suzuki
Biographic Data
| ID | 6029898 |
|---|---|
| NAME | Takuro Suzuki |
| GIVEN NAMES | Takuro |
| FAMILY NAME | Suzuki |
| SIGNATURE | SUZUKI T |
| AFFILIATIONS | University of Toyama |
| VERIFIED | No |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Examining factors predicting formal help-seeking behavior in stalking victims using Bayesian networks
A survey on the reasons why victims of stalking did not exhibit help-seeking behavior
The identification of gender stereotype-related reasons among male victims was a valuable insight that could only be obtained through comparison with female victims. However, the study was limited to addressing the individual characteristics of the cases, thus providing only hypothetical insights into general trends. In future research, it will be necessary to generate hypotheses from the findings of this study and accumulate hypothesis-testing r…
Classifying perpetrators of stalking-related behavior with latent class analysis
Stalking often escalates from mild behaviors, such as surveillance, to severe forms involving violence, posing serious risks to victims. While identifying high-risk perpetrator classes is crucial for preventing victimization, research on perpetrator classification based on stalking behavior remains limited. This study used latent class analysis (LCA) to classify perpetrators by gender based on their stalking-related behavior (SRB) patterns from a…
No prominent works on this page.
A survey on the reasons why victims of stalking did not exhibit help-seeking behavior
The identification of gender stereotype-related reasons among male victims was a valuable insight that could only be obtained through comparison with female victims. However, the study was limited to addressing the individual characteristics of the cases, thus providing only hypothetical insights into general trends. In future research, it will be necessary to generate hypotheses from the findings of this study and accumulate hypothesis-testing r…
Classifying perpetrators of stalking-related behavior with latent class analysis
Stalking often escalates from mild behaviors, such as surveillance, to severe forms involving violence, posing serious risks to victims. While identifying high-risk perpetrator classes is crucial for preventing victimization, research on perpetrator classification based on stalking behavior remains limited. This study used latent class analysis (LCA) to classify perpetrators by gender based on their stalking-related behavior (SRB) patterns from a…
Examining factors predicting formal help-seeking behavior in stalking victims using Bayesian networks
Stalking (3 works) · Stalking, Cyberstalking, and Harassment (3 works) · Criminology (2 works) · Psychology (2 works) · Sexuality, Behavior, and Technology (2 works) · Social Psychology (2 works) · Social Psychology (2 works) · Applied Psychology (1 work) · Applied Psychology (1 work) · Artificial Intelligence (1 work)