Modeling ReTweet Diffusion Using Emotional Content

Abstract : In this paper we present a prediction model for forecasting the depth and the width of ReTweeting using data mining techniques. The proposed model utilizes the analyzers of tweet emotional content based on Ekman emotional model, as well as the behavior of users in Twitter. In following, our model predicts the category of ReTweeting diffusion. The model was trained and validated with real data crawled by Twitter. The aim of this model is the estimation of spreading of a new post which could be retweeted by the users in a particular network. The classification model is intended as a tool for sponsors and people of marketing to specify the tweets that spread more in Twitter network.
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Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 10th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2014, Rhodes, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-436, pp.101-110, 2014, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-662-44654-6_10〉
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Andreas Kanavos, Isidoros Perikos, Pantelis Vikatos, Ioannis Hatzilygeroudis, Christos Makris, et al.. Modeling ReTweet Diffusion Using Emotional Content. Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 10th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2014, Rhodes, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-436, pp.101-110, 2014, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-662-44654-6_10〉. 〈hal-01391297〉

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