{"title":"基于GNN模型的实时转发数预测","authors":"Cheng-Ta Lo, Yi-Hsuan Lee, Jun-Hong Peng","doi":"10.1109/ICASI57738.2023.10179521","DOIUrl":null,"url":null,"abstract":"Twitter users usually care about the popularity of their tweets, and retweet count is always a good measure. Along with Neural Networks have achieved outstanding accomplishments, Graph Neural Network (GNN) becomes a new research field. In this article, we select a group of active users on a Twitter page. After observing their recent retweet behaviors, different GNN models are constructed and labeled. These GNN models are used to predict the user retweet behavior and estimate the retweet count in the early stage.","PeriodicalId":281254,"journal":{"name":"2023 9th International Conference on Applied System Innovation (ICASI)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Real-time Retweet Count Prediction using GNN Model\",\"authors\":\"Cheng-Ta Lo, Yi-Hsuan Lee, Jun-Hong Peng\",\"doi\":\"10.1109/ICASI57738.2023.10179521\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Twitter users usually care about the popularity of their tweets, and retweet count is always a good measure. Along with Neural Networks have achieved outstanding accomplishments, Graph Neural Network (GNN) becomes a new research field. In this article, we select a group of active users on a Twitter page. After observing their recent retweet behaviors, different GNN models are constructed and labeled. These GNN models are used to predict the user retweet behavior and estimate the retweet count in the early stage.\",\"PeriodicalId\":281254,\"journal\":{\"name\":\"2023 9th International Conference on Applied System Innovation (ICASI)\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 9th International Conference on Applied System Innovation (ICASI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICASI57738.2023.10179521\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 9th International Conference on Applied System Innovation (ICASI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASI57738.2023.10179521","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Real-time Retweet Count Prediction using GNN Model
Twitter users usually care about the popularity of their tweets, and retweet count is always a good measure. Along with Neural Networks have achieved outstanding accomplishments, Graph Neural Network (GNN) becomes a new research field. In this article, we select a group of active users on a Twitter page. After observing their recent retweet behaviors, different GNN models are constructed and labeled. These GNN models are used to predict the user retweet behavior and estimate the retweet count in the early stage.