{"title":"网络社区意见分析的群体智能","authors":"Carolin Kaiser, Johannes Kröckel, F. Bodendorf","doi":"10.1109/HICSS.2010.356","DOIUrl":null,"url":null,"abstract":"Web 2.0 platforms change the collaboration within online communities. A new way of organizing and opinion exchanging derives from increased social interactions and networking among community members. These members join together in self-organizing groups where opinions are forming by social swarming. Explaining and predicting the evolutionary process of opinion formation by social swarming is not only a powerful instrument for opinion research but also a great challenge. A new approach is presented which enables the recognition of opinions of swarm members and the analysis of opinion formation in the overall swarm by combining methods from text mining and swarm intelligence. The concept is illustrated by an example.","PeriodicalId":328811,"journal":{"name":"2010 43rd Hawaii International Conference on System Sciences","volume":"55 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"Swarm Intelligence for Analyzing Opinions in Online Communities\",\"authors\":\"Carolin Kaiser, Johannes Kröckel, F. Bodendorf\",\"doi\":\"10.1109/HICSS.2010.356\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Web 2.0 platforms change the collaboration within online communities. A new way of organizing and opinion exchanging derives from increased social interactions and networking among community members. These members join together in self-organizing groups where opinions are forming by social swarming. Explaining and predicting the evolutionary process of opinion formation by social swarming is not only a powerful instrument for opinion research but also a great challenge. A new approach is presented which enables the recognition of opinions of swarm members and the analysis of opinion formation in the overall swarm by combining methods from text mining and swarm intelligence. The concept is illustrated by an example.\",\"PeriodicalId\":328811,\"journal\":{\"name\":\"2010 43rd Hawaii International Conference on System Sciences\",\"volume\":\"55 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-01-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 43rd Hawaii International Conference on System Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HICSS.2010.356\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 43rd Hawaii International Conference on System Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HICSS.2010.356","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19
摘要
Web 2.0平台改变了在线社区内的协作。一种新的组织和意见交流方式源于社区成员之间社会互动和网络的增加。这些成员加入到自组织群体中,通过社会群体形成意见。解释和预测社会群体意见形成的演化过程是民意研究的有力工具,也是一个巨大的挑战。将文本挖掘和群体智能相结合,提出了一种识别群体成员意见并分析群体整体意见形成的新方法。这个概念是通过一个例子来说明的。
Swarm Intelligence for Analyzing Opinions in Online Communities
Web 2.0 platforms change the collaboration within online communities. A new way of organizing and opinion exchanging derives from increased social interactions and networking among community members. These members join together in self-organizing groups where opinions are forming by social swarming. Explaining and predicting the evolutionary process of opinion formation by social swarming is not only a powerful instrument for opinion research but also a great challenge. A new approach is presented which enables the recognition of opinions of swarm members and the analysis of opinion formation in the overall swarm by combining methods from text mining and swarm intelligence. The concept is illustrated by an example.