Abstract
An efficient tweet dissemination predictor for retweets and replies is central both to a better understanding of influentials (people and messages), as well as of how social media revenue models can be better monetized. Traditionally research concentrated on retweets popularity and information cascades while neglecting the importance of features richness and classification. We propose a novel approach that introduces feature planes for better prediction of single step tweet dissemination. We show that our model can achieve a quasi-perfect prediction. This promises to be a seminal step towards a better understanding of data dissemination in social networks.
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Garg, K., Arnaboldi, V., Giordano, S. (2017). A Novel Approach to Predict Retweets and Replies Based on Privacy and Complexity-Aware Feature Planes. In: Cherifi, H., Gaito, S., Quattrociocchi, W., Sala, A. (eds) Complex Networks & Their Applications V. COMPLEX NETWORKS 2016 2016. Studies in Computational Intelligence, vol 693. Springer, Cham. https://doi.org/10.1007/978-3-319-50901-3_37
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DOI: https://doi.org/10.1007/978-3-319-50901-3_37
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