AN EFFECTIVE SYSTEM TO IMPROVE THE CYBERBULLYING
@inproceedings{Divyashree2016ANES, title={AN EFFECTIVE SYSTEM TO IMPROVE THE CYBERBULLYING}, author={Divyashree and H M Vinutha and S DeepashreeN}, year={2016} }
The rapid growth of social networking is supplementing the progression of cyberbullying activities. Most of the individuals involved in these activities belong to the younger generations, especially teenagers, who in the worst scenario are at more risk of suicidal attempts. This propose an effective approach to detect cyberbullying messages from social media through a SVM classifier algorithm. This present ranking algorithm to access highest visited link and also provide age verification…
No Paper Link Available
One Citation
Analysis of Cyberbullying Incidence among Filipina Victims: A Pattern Recognition using Association Rule Extraction
- Computer ScienceInternational Journal of Intelligent Systems and Applications
- 2019
The study revealed that the type of dominant frequent cyberbullying words are intelligence, personality, and insulting words that describe the behavior, appearance of the female victims and sex related words that humiliate female victims.
References
SHOWING 1-10 OF 27 REFERENCES
An Effective Approach for Cyberbullying Detection
- Computer Science
- 2013
An effective approach to detect cyberbullying messages from social media through a weighting scheme of feature selection is proposed and a graph model is presented to extract the cyberBullying network, which is used to identify the most active cyberbullies predators and victims through ranking algorithms.
Improved cyberbullying detection using gender information
- Computer Science
- 2012
It is demonstrated that taking gender-specific language features into account improves the discrimination capacity of a classifier to detect cyberbullying.
Towards understanding cyberbullying behavior in a semi-anonymous social network
- Computer Science2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)
- 2014
Cyberbullying has emerged as an important and growing social problem, wherein people use online social networks and mobile phones to bully victims with offensive text, images, audio and video on a…
Cyberbullying detection: a step toward a safer internet yard
- Computer ScienceWWW
- 2012
This work proposes that incorporation of the users' information, their characteristics, and post-harassing behaviour, for instance, posting a new status in another social network as a reaction to their bullying experience, will improve the accuracy of cyberbullying detection.
Automatic Detection of Cyberbullying to Make Internet a Safer Environment
- Computer Science
- 2017
This chapter discusses current and potential applications of text mining techniques for the detection of cyberbullying and reviews existing research in dealing with this phenomenon.
Machine learning approach for detection of cyber-aggressive comments by peers on social media network
- Computer Science2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI)
- 2015
Methods to detect cyberbullying using supervised learning techniques are devised and two new hypotheses for feature extraction to detect offensive comments directed towards peers which are perceived more negatively and result in cyberbullies are presented.
Expert knowledge for automatic detection of bullies in social networks
- Computer Science
- 2013
A multi-criteria evaluation system is used to obtain a better understanding of YouTube users’ behaviour and their characteristics through expert knowledge, which represents their level of “bulliness” based on the history of their activities.
Let's Gang Up on Cyberbullying
- PsychologyComputer
- 2011
The novel design of social network software that can help prevent and manage the growing problem of cyberbullying are discussed.
Common Sense Reasoning for Detection, Prevention, and Mitigation of Cyberbullying
- Computer ScienceTIIS
- 2012
An “air traffic control”-like dashboard is proposed, which alerts moderators to large-scale outbreaks that appear to be escalating or spreading and helps them prioritize the current deluge of user complaints.