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Arabian Journal for Science and Engineering
Published in: Arabian Journal for Science and Engineering 2/2022

09-09-2021 | Research Article-Computer Engineering and Computer Science

A Framework for Video Popularity Forecast Utilizing Metaheuristic Algorithms

Authors: Neeti Sangwan, Vishal Bhatnagar

Published in: Arabian Journal for Science and Engineering | Issue 2/2022

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Abstract

Data available online is growing day by day that leads to a tough competition among data publishers to attract the largest possible audience. Obtaining reliable prediction related to future popularity of the online content becomes a concern to the publishers. In this paper, a novel nature-inspired metaheuristic framework is proposed that shortlists the prominent features of the video to participate in making predictions. Fitness of the set of selected features is calculated using mean square error of the deviation between predicted and actual popularity. The exhaustive examinations on standard benchmark parameters is performed on the datasets, i.e., Facebook 2015, Top and random datasets of YouTube. The performance of the proposed algorithms, namely particle swarm optimization with support vector regression (PSO-SVR), bat algorithm with support vector regression (BA-SVR), dragonfly algorithm with support vector regression (DA-SVR) and existing prediction method support vector regression (SVR), is compared. DA-SVR outperforms SVR, PSO-SVR and BA-SVR in terms of coefficient of regularization (R2) score and number of features selected.
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Metadata
Title
A Framework for Video Popularity Forecast Utilizing Metaheuristic Algorithms
Authors
Neeti Sangwan
Vishal Bhatnagar
Publication date
09-09-2021
Publisher
Springer Berlin Heidelberg
Published in
Arabian Journal for Science and Engineering / Issue 2/2022
Print ISSN: 2193-567X
Electronic ISSN: 2191-4281
DOI
https://doi.org/10.1007/s13369-021-06146-w

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