Deep Learning Algorithm for Cyberbullying Detection
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2018, Vol 9, Issue 9
Abstract
Cyberbullying is a crime where one person becomes the target of harassment and hate. Many cyberbullying detection approaches have been introduced, however, they were largely based on textual and user features. Most of the research found in the literature aimed at improving detection through introducing new features. However, as the number of features increases, the feature extraction and selection phases have become harder. On the other hand, no study has examined the meaning of words and semantics in cyberbullying. In order to bridge this gap, we propose a novel algorithms CNN-CB that eliminate the need for feature engineering and produce better prediction than traditional cyberbullying detection approaches. The proposed algorithm adapts the concept of word embedding where similar words have similar embedding. Therefore, bullying tweets will have similar representations and this will advance the detection. CNN-CB is based on convolutional neural network (CNN) and incorporates semantics through the use of word embedding. Experiments showed that CNN-CB algorithm outperform traditional content-based cyberbullying detection with an accuracy of 95%.
Authors and Affiliations
Monirah Abdullah Al-Ajlan, Mourad Ykhlef
Smart Surveillance System using Background Subtraction Technique in IoT Application
This paper presents a development of a security system based on Internet-of-Things (IoT) technology, where an IoT device, Raspberry Pi has been used. In the developed surveillance system, a camera works as a sensor to de...
Loop Modeling Forward and Feedback Analysis in Cerebral Arteriovenous Malformation
Cerebral Arteriovenous Malformation (CAVM) hemodynamic in disease condition results changes in the flow and pressure level in blood vessels. Cerebral Arteriovenous Malformation (CAVM) is an abnormal shunting of vessels b...
Timed-Arc Petri-Nets based Agent Communication for Real-Time Multi-Agent Systems
This research focuses on Timed-Arc Petri-nets-based agent communication in real-time multi-agent systems. The Agent Communication Language is a standard language for the agents to communicate. The objective is to combine...
A Globally Convergent Algorithm of Variational Inequality
The algorithm of variational inequality is the important and valuable question in real life all the time. In this paper, a globally convergent algorithm of variational inequality is proposed. The method ensures tha...
Spectral Efficiency of Massive MIMO Communication Systems with Zero Forcing and Maximum Ratio Beamforming
The massive multiple-input-multiple-output (MIMO) is a key enabling technology for the 5G cellular communication systems. In massive MIMO (M-MIMO) systems few hundred numbers of antennas are deployed at each base station...