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Volumn , Issue , 2011, Pages 838-843

Estimating twitter user location using social interactions - A content based approach

Author keywords

Content based location estimation; Data mining; Social interaction; Twitter

Indexed keywords

BASELINE ESTIMATION; CONTENT-BASED APPROACH; LOCATION ESTIMATION; LOCATION INFORMATION; MICROBLOGGING; PROBABILISTIC FRAMEWORK; PROBABILITY ESTIMATE; SOCIAL INTERACTION; SOCIAL INTERACTIONS; SOCIAL NETWORKS; STATE OF THE ART; TWITTER; USER LOCATION;

EID: 84856148239     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/PASSAT/SocialCom.2011.120     Document Type: Conference Paper
Times cited : (117)

References (13)
  • 1
    • 77954590940 scopus 로고    scopus 로고
    • Find me if you can: Improving geographical prediction with social and spatial proximity
    • L. Backstrom, E. Sun, and C. Marlow. Find me if you can: improving geographical prediction with social and spatial proximity. In WWW, 2010.
    • (2010) WWW
    • Backstrom, L.1    Sun, E.2    Marlow, C.3
  • 5
    • 78649269065 scopus 로고    scopus 로고
    • TweetHood: Agglomorative clustering on fuzzy k-closest friends with variable depth for location mining
    • S. Abrol and L. Khan. TweetHood: Agglomorative Clustering on Fuzzy k-Closest Friends with Variable depth for Location Mining. SocialCom/PASSAT 2010: 153-160.
    • (2010) SocialCom/PASSAT , pp. 153-160
    • Abrol, S.1    Khan, L.2
  • 12
    • 58449115775 scopus 로고    scopus 로고
    • Social networks that matter: Twitter under the microscope
    • B. Huberman and D. R. F. Wu. Social networks that matter: Twitter under the microscope. First Monday, 14, 2009.
    • (2009) First Monday , vol.14
    • Huberman, B.1    Wu, D.R.F.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.