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Journal of Combinatorial Optimization

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03-01-2021

Group level social media popularity prediction by MRGB and Adam optimization

Authors: Navdeep Bohra, Vishal Bhatnagar

Published in: Journal of Combinatorial Optimization | Issue 2/2021

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Abstract

Social media has become a tremendous source to bring in new clients. Sharing posts for new offers/products to get extensive client engagement can be predicted by grouping the users based on their previous interactions. In this paper, we improve existing state-of-the-art techniques to predict group-level popularity by extending the data clustering approach and constraint network prediction using stochastic Adam optimization. Various other topological properties of this two-level approach are also tested. The Adam optimization for clustered group prediction improves the relative error substantially. Overall, the proposed novel approach improved the prediction popularity accuracy by a significant difference of 18.21%.

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Title: Group level social media popularity prediction by MRGB and Adam optimization
Authors: Navdeep Bohra
Vishal Bhatnagar
Publication date: 03-01-2021
Publisher: Springer US
Published in: Journal of Combinatorial Optimization / Issue 2/2021
Print ISSN: 1382-6905
Electronic ISSN: 1573-2886
DOI: https://doi.org/10.1007/s10878-020-00684-z

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