Abstract
Cyberbullying is the deliberate use of online digital media to communicate false, embarrassing, or hostile information about another person. It is the most common online risk for adolescents and well over half of young people do not tell their parents when it occurs. While there have been many studies about the nature and prevalence of cyberbullying, there has been relatively less work in the area of automated identification of cyberbullying in social media sites. The focus of our work is to develop an automated model to identify and measure the degree of cyberbullying in social networking sites, and a Facebook app for parents, built on this model, that notifies them when cyberbullying occurs. This paper describes the challenges associated with building a computer model for cyberbullying identification, presents key results from psychology research that can be used in such a model, describes an initial model and mobile app design for cyberbullying identification, and describes key areas of future work to improve upon the initial model.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 1377-1379 |
| Number of pages | 3 |
| ISBN (Electronic) | 9781509028467 |
| DOIs | |
| State | Published - Nov 21 2016 |
| Event | 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 - San Francisco, United States Duration: Aug 18 2016 → Aug 21 2016 |
Other
| Other | 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 |
|---|---|
| Country | United States |
| City | San Francisco |
| Period | 8/18/16 → 8/21/16 |
Fingerprint
Keywords
- automated identification
- cyberbullying
- social networks
ASJC Scopus subject areas
- Computer Networks and Communications
- Sociology and Political Science
- Communication
Cite this
BullyBlocker : Towards the identification of cyberbullying in social networking sites. / Silva, Yasin; Rich, Christopher; Hall, Deborah.
Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 1377-1379 7752420.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - BullyBlocker
T2 - Towards the identification of cyberbullying in social networking sites
AU - Silva, Yasin
AU - Rich, Christopher
AU - Hall, Deborah
PY - 2016/11/21
Y1 - 2016/11/21
N2 - Cyberbullying is the deliberate use of online digital media to communicate false, embarrassing, or hostile information about another person. It is the most common online risk for adolescents and well over half of young people do not tell their parents when it occurs. While there have been many studies about the nature and prevalence of cyberbullying, there has been relatively less work in the area of automated identification of cyberbullying in social media sites. The focus of our work is to develop an automated model to identify and measure the degree of cyberbullying in social networking sites, and a Facebook app for parents, built on this model, that notifies them when cyberbullying occurs. This paper describes the challenges associated with building a computer model for cyberbullying identification, presents key results from psychology research that can be used in such a model, describes an initial model and mobile app design for cyberbullying identification, and describes key areas of future work to improve upon the initial model.
AB - Cyberbullying is the deliberate use of online digital media to communicate false, embarrassing, or hostile information about another person. It is the most common online risk for adolescents and well over half of young people do not tell their parents when it occurs. While there have been many studies about the nature and prevalence of cyberbullying, there has been relatively less work in the area of automated identification of cyberbullying in social media sites. The focus of our work is to develop an automated model to identify and measure the degree of cyberbullying in social networking sites, and a Facebook app for parents, built on this model, that notifies them when cyberbullying occurs. This paper describes the challenges associated with building a computer model for cyberbullying identification, presents key results from psychology research that can be used in such a model, describes an initial model and mobile app design for cyberbullying identification, and describes key areas of future work to improve upon the initial model.
KW - automated identification
KW - cyberbullying
KW - Facebook
KW - social networks
UR - http://www.scopus.com/inward/record.url?scp=85006837032&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85006837032&partnerID=8YFLogxK
U2 - 10.1109/ASONAM.2016.7752420
DO - 10.1109/ASONAM.2016.7752420
M3 - Conference contribution
AN - SCOPUS:85006837032
SP - 1377
EP - 1379
BT - Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016
PB - Institute of Electrical and Electronics Engineers Inc.
ER -