{"title":"Location inference using microblog text and friendships","authors":"Chuanyang Li, Xiuqin Lin, Bin Wu, C. Shi","doi":"10.1109/ASONAM.2014.6921674","DOIUrl":null,"url":null,"abstract":"In this paper, we proposed a novel scheme to infer user's location using microblog text and friendships, without known geo information. The major part of our research is identifying local words, words that associated with some particular location. With local words we identified, we use conditional random fields (CRF), to detect location specific microblog. Then we can estimate the most possible location of a user. And we take advantage of users' friendships to improve the result. Another key feature of our approach is that we consider timeliness of local words, as some local words are descriptions of local events and they are only associated with location during a certain period of time. Experimental evidence suggests that our algorithm works well in practice and outperforms the existing algorithms for estimating the location of microblog users.","PeriodicalId":143584,"journal":{"name":"2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASONAM.2014.6921674","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
In this paper, we proposed a novel scheme to infer user's location using microblog text and friendships, without known geo information. The major part of our research is identifying local words, words that associated with some particular location. With local words we identified, we use conditional random fields (CRF), to detect location specific microblog. Then we can estimate the most possible location of a user. And we take advantage of users' friendships to improve the result. Another key feature of our approach is that we consider timeliness of local words, as some local words are descriptions of local events and they are only associated with location during a certain period of time. Experimental evidence suggests that our algorithm works well in practice and outperforms the existing algorithms for estimating the location of microblog users.