Modeling ReTweet Diffusion Using Emotional Content - Artificial Intelligence Applications and Innovations (AIAI 2014) Access content directly
Conference Papers Year : 2014

Modeling ReTweet Diffusion Using Emotional Content

Andreas Kanavos
  • Function : Author
  • PersonId : 992416
Isidoros Perikos
  • Function : Author
  • PersonId : 992420
Pantelis Vikatos
  • Function : Author
  • PersonId : 992417
Ioannis Hatzilygeroudis
  • Function : Author
  • PersonId : 992421
Christos Makris
  • Function : Author
  • PersonId : 992346
Athanasios Tsakalidis
  • Function : Author
  • PersonId : 992342

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.
Fichier principal
Vignette du fichier
978-3-662-44654-6_10_Chapter.pdf (275.89 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01391297 , version 1 (03-11-2016)

Licence

Attribution

Identifiers

Cite

Andreas Kanavos, Isidoros Perikos, Pantelis Vikatos, Ioannis Hatzilygeroudis, Christos Makris, et al.. Modeling ReTweet Diffusion Using Emotional Content. 10th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2014, Rhodes, Greece. pp.101-110, ⟨10.1007/978-3-662-44654-6_10⟩. ⟨hal-01391297⟩
73 View
434 Download

Altmetric

Share

Gmail Facebook X LinkedIn More