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

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    Publication date
    2021
    End of Embargo
    2022
    Author
    Kumari, K.
    Singh, J.P.
    Dwivedi, Y.K.
    Rana, Nripendra P.
    Keyword
    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/)
    Peer-Reviewed
    Yes
    
    Metadata
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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. Accepted for publication.
    Type
    Article
    Notes
    The full-text of this article will be released for public view at the end of the publisher embargo, 12 months from first publication.
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    Management and Law Publications

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