{"title":"Micro-Blog Influence Evaluation Method Based on Particle Swarm Optimization Algorithm","authors":"Song Junyuan","doi":"10.1109/ICRIS.2017.58","DOIUrl":null,"url":null,"abstract":"Micro-blog is regarded as one of the most popular platforms for information sharing based on Web 2.0 technology. In this paper, we propose a novel Micro-blog influence evaluation method by modeling users' behaviors in Micro-blog platform. Firstly, considering the Micro-blog API data capture method program is simple, we aim to achieve a higher efficiency and consistency of data crawling by relieving the API access frequency limit. Secondly, inspired by the fact that a follower who has higher influence can effectively spread his tweets than the one with lower influence, we propose a particle swarm optimization based Micro-blog influence evaluation method. Finally, experimental results demonstrate that the proposed PSO based algorithm is able to estimate the Micro-blog user influence with high accuracy.","PeriodicalId":443064,"journal":{"name":"2017 International Conference on Robots & Intelligent System (ICRIS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Robots & Intelligent System (ICRIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRIS.2017.58","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Micro-blog is regarded as one of the most popular platforms for information sharing based on Web 2.0 technology. In this paper, we propose a novel Micro-blog influence evaluation method by modeling users' behaviors in Micro-blog platform. Firstly, considering the Micro-blog API data capture method program is simple, we aim to achieve a higher efficiency and consistency of data crawling by relieving the API access frequency limit. Secondly, inspired by the fact that a follower who has higher influence can effectively spread his tweets than the one with lower influence, we propose a particle swarm optimization based Micro-blog influence evaluation method. Finally, experimental results demonstrate that the proposed PSO based algorithm is able to estimate the Micro-blog user influence with high accuracy.