Laura Dietz, Ziqi Wang, Samuel Huston, W. Bruce Croft
{"title":"从论坛中检索意见","authors":"Laura Dietz, Ziqi Wang, Samuel Huston, W. Bruce Croft","doi":"10.1145/2505515.2507861","DOIUrl":null,"url":null,"abstract":"Abstract Understanding the landscape of opinions on a given topic or issue is important for policy makers, sociologists, and intelligence analysts. The first step in this process is to retrieve relevant opinions. Discussion forums are potentially a good source of this information, but comes with a unique set of retrieval challenges. In this short paper, we test a range of existing techniques for forum retrieval and develop new retrieval models to differentiate between opinionated and factual forum posts. We are able to demonstrate some significant performance improvements over the baseline retrieval models, demonstrating that this as a promising avenue for further study.","PeriodicalId":20528,"journal":{"name":"Proceedings of the 22nd ACM international conference on Information & Knowledge Management","volume":"75 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2013-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Retrieving opinions from discussion forums\",\"authors\":\"Laura Dietz, Ziqi Wang, Samuel Huston, W. Bruce Croft\",\"doi\":\"10.1145/2505515.2507861\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Understanding the landscape of opinions on a given topic or issue is important for policy makers, sociologists, and intelligence analysts. The first step in this process is to retrieve relevant opinions. Discussion forums are potentially a good source of this information, but comes with a unique set of retrieval challenges. In this short paper, we test a range of existing techniques for forum retrieval and develop new retrieval models to differentiate between opinionated and factual forum posts. We are able to demonstrate some significant performance improvements over the baseline retrieval models, demonstrating that this as a promising avenue for further study.\",\"PeriodicalId\":20528,\"journal\":{\"name\":\"Proceedings of the 22nd ACM international conference on Information & Knowledge Management\",\"volume\":\"75 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 22nd ACM international conference on Information & Knowledge Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2505515.2507861\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 22nd ACM international conference on Information & Knowledge Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2505515.2507861","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Abstract Understanding the landscape of opinions on a given topic or issue is important for policy makers, sociologists, and intelligence analysts. The first step in this process is to retrieve relevant opinions. Discussion forums are potentially a good source of this information, but comes with a unique set of retrieval challenges. In this short paper, we test a range of existing techniques for forum retrieval and develop new retrieval models to differentiate between opinionated and factual forum posts. We are able to demonstrate some significant performance improvements over the baseline retrieval models, demonstrating that this as a promising avenue for further study.