{"title":"构建Facebook页面的关键字传播图","authors":"Soraya Chalard, S. Sinthupinyo","doi":"10.1109/ECAI46879.2019.9042080","DOIUrl":null,"url":null,"abstract":"Social network visualization has been extensively studied in research in diffusion of information. This paper focuses on extracting propagated Facebook posts from keywords created by users and visualizing important information diffusion path in social network graph. Furthermore, some interesting propagation patterns of user behavior in online social network were discovered. Our research contributions could be summarized as follow: 1) A novel method was proposed to determine the keyword occurrence in online social network, 2) This research constructed the map of keyword propagation and visualized the propagation patterns among different groups of people and 3) a case study of social phenomena was shown. In sum, our work eventually could be applied to improve the performance of tracking keyword spread in social media and would be beneficial for greater understanding about user behavior.","PeriodicalId":285780,"journal":{"name":"2019 11th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)","volume":"229 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Constructing Keyword Propagation Map of Facebook Pages\",\"authors\":\"Soraya Chalard, S. Sinthupinyo\",\"doi\":\"10.1109/ECAI46879.2019.9042080\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Social network visualization has been extensively studied in research in diffusion of information. This paper focuses on extracting propagated Facebook posts from keywords created by users and visualizing important information diffusion path in social network graph. Furthermore, some interesting propagation patterns of user behavior in online social network were discovered. Our research contributions could be summarized as follow: 1) A novel method was proposed to determine the keyword occurrence in online social network, 2) This research constructed the map of keyword propagation and visualized the propagation patterns among different groups of people and 3) a case study of social phenomena was shown. In sum, our work eventually could be applied to improve the performance of tracking keyword spread in social media and would be beneficial for greater understanding about user behavior.\",\"PeriodicalId\":285780,\"journal\":{\"name\":\"2019 11th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)\",\"volume\":\"229 2\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 11th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ECAI46879.2019.9042080\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 11th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECAI46879.2019.9042080","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Constructing Keyword Propagation Map of Facebook Pages
Social network visualization has been extensively studied in research in diffusion of information. This paper focuses on extracting propagated Facebook posts from keywords created by users and visualizing important information diffusion path in social network graph. Furthermore, some interesting propagation patterns of user behavior in online social network were discovered. Our research contributions could be summarized as follow: 1) A novel method was proposed to determine the keyword occurrence in online social network, 2) This research constructed the map of keyword propagation and visualized the propagation patterns among different groups of people and 3) a case study of social phenomena was shown. In sum, our work eventually could be applied to improve the performance of tracking keyword spread in social media and would be beneficial for greater understanding about user behavior.