Abstract
Today’s social networks allow users to react to new contents such as images, posts and messages in numerous ways. For example, a user, impressed by another user’s post, might react to it by liking it and then sharing it forward to her friends. Therefore, a successful estimation of the influence between users requires models to be expressive enough to fully describe various reactions. In this article, we aim to utilize those direct reactive activities, in order to calculate users impact on others. Hence, we propose a flexible method that considers type, quality, quantity and time of reactions and, as a result, the method assesses the influence dependencies within the social network. The experiments conducted using two different real-world datasets of Facebook and Pinterest show the adequacy and flexibility of the proposed model that is adaptive to data having different features.
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Notes
- 1.
In the Action-Reaction schema, we refer to an Action as a self-activity of user u, while Reactions symbolize activities overtaken by other users in response to the user u Action.
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Rakoczy, M.E., Bouzeghoub, A., Wegrzyn-Wolska, K., Gancarski, A.L. (2019). Exploring Interactions in Social Networks for Influence Discovery. In: Abramowicz, W., Corchuelo, R. (eds) Business Information Systems. BIS 2019. Lecture Notes in Business Information Processing, vol 354. Springer, Cham. https://doi.org/10.1007/978-3-030-20482-2_3
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DOI: https://doi.org/10.1007/978-3-030-20482-2_3
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