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Multi-modal Aggression Identification Using Convolutional Neural Network and Binary Particle Swarm Optimization

Kumari, K.
; 
Singh, J.P.
; 
Dwivedi, Y.K.
; 
Rana, Nripendra P.
Publication Date
2021-05
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Keywords
Cyber-aggression, Cyberbullying, Multi-modal data, Convolutional neural network, Binary particle swarm optimisation
Rights
© 2021 Elsevier. Reproduced in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license (https://creativecommons.org/licenses/by-nc-nd/4.0/)
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Yes
Open Access status
openAccess
Accepted for publication
10/01/2021
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Management and Law Publications
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Abstract
Aggressive posts containing symbolic and offensive images, inappropriate gestures along with provocative textual comments are growing exponentially in social media with the availability of inexpensive data services. These posts have numerous negative impacts on the reader and need an immediate technical solution to filter out aggressive comments. This paper presents a model based on a Convolutional Neural Network (CNN) and Binary Particle Swarm Optimization (BPSO) to classify the social media posts containing images with associated textual comments into non-aggressive, medium-aggressive and high-aggressive classes. A dataset containing symbolic images and the corresponding textual comments was created to validate the proposed model. The framework employs a pre-trained VGG-16 to extract the image features and a three-layered CNN to extract the textual features in parallel. The hybrid feature set obtained by concatenating the image and the text features were optimized using the BPSO algorithm to extract the more relevant features. The proposed model with optimized features and Random Forest classifier achieves a weighted F1-Score of 0.74, an improvement of around 3% over unoptimized features.
URI
http://hdl.handle.net/10454/18300
Version
Accepted manuscript
Citation
Kumari K, Singh JP, Dwivedi YK et al (2021) Multi-modal Aggression Identification Using Convolutional Neural Network and Binary Particle Swarm Optimization. Future Generation Computer Systems. 118: 187-197.
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Link to published version
Link to Version of Record
https://doi.org/10.1016/j.future.2021.01.014
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Article
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