Abstract
Information diffusion is employed to track the spread of information in the online social network, and hence, is considered extremely relevant to several modern-day applications. It is of pivotal importance for addressing challenges associated with the influence maximization in social media. Our research focuses on the diffusion process to track the temporal extent of information spread in the network. Over time, various models have been suggested in order to best represent the diffusion process. Our paper suggests a novel information diffusion model, time-aware opinion dynamics model (TODD), that derives from opinion dynamics and continuous time models in order to provide a more robust and realistic representation of the real-world problem. A comparative study is conducted between our proposed model and several existing methods.
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Lahiri, A., Singhal, Y.K., Sinha, A. (2021). TODD: Time-Aware Opinion Dynamics Diffusion Model for Online Social Networks. In: Bansal, P., Tushir, M., Balas, V., Srivastava, R. (eds) Proceedings of International Conference on Artificial Intelligence and Applications. Advances in Intelligent Systems and Computing, vol 1164. Springer, Singapore. https://doi.org/10.1007/978-981-15-4992-2_23
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DOI: https://doi.org/10.1007/978-981-15-4992-2_23
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