TY - JOUR
T1 - Session-Based Cyberbullying Detection
T2 - Problems and Challenges
AU - Cheng, Lu
AU - Silva, Yasin N.
AU - Hall, Deborah
AU - Liu, Huan
N1 - Funding Information:
This work was supported by the National Science Foundation under Grants 1719722, 1614576, and 2036127.
Publisher Copyright:
© 1997-2012 IEEE.
PY - 2021/3/1
Y1 - 2021/3/1
N2 - Cyberbullying has become one of the most pressing online risks for young people, due in part to the rapid increase in social media use, and has raised serious concerns in society. Existing studies have examined various approaches to cyberbullying detection focusing on a single piece of text, whereas relatively little is known about cyberbullying detection within a social media session. A social media session typically consists of an initial post, images/videos, a sequence of comments that involves user interactions, user information, spatial location, and other social content. By investigating cyberbullying at the level of social media sessions, researchers can draw on data that are more complex, diverse, and crucial for understanding two defining characteristics of cyberbullying, in particular: repetitive acts and power imbalance. This article thus highlights the importance of studying session-based cyberbullying detection, identifies core challenges, and serves as a resource to help direct future research efforts.
AB - Cyberbullying has become one of the most pressing online risks for young people, due in part to the rapid increase in social media use, and has raised serious concerns in society. Existing studies have examined various approaches to cyberbullying detection focusing on a single piece of text, whereas relatively little is known about cyberbullying detection within a social media session. A social media session typically consists of an initial post, images/videos, a sequence of comments that involves user interactions, user information, spatial location, and other social content. By investigating cyberbullying at the level of social media sessions, researchers can draw on data that are more complex, diverse, and crucial for understanding two defining characteristics of cyberbullying, in particular: repetitive acts and power imbalance. This article thus highlights the importance of studying session-based cyberbullying detection, identifies core challenges, and serves as a resource to help direct future research efforts.
UR - http://www.scopus.com/inward/record.url?scp=85096137665&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85096137665&partnerID=8YFLogxK
U2 - 10.1109/MIC.2020.3032930
DO - 10.1109/MIC.2020.3032930
M3 - Article
AN - SCOPUS:85096137665
SN - 1089-7801
VL - 25
SP - 66
EP - 72
JO - IEEE Internet Computing
JF - IEEE Internet Computing
IS - 2
M1 - 9237088
ER -