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Volumn 222 CCIS, Issue , 2012, Pages 319-333

Machine learning for the detection of spam in twitter networks

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN CLASSIFIER; CLASSIFICATION METHODS; CONTENT-BASED FEATURES; DATA SETS; DETECTION SYSTEM; EVALUATION METRICS; F-MEASURE; GRAPH-BASED; PROTOTYPE SYSTEM; SOCIAL GRAPHS; SOCIAL NETWORKING SITES; SPAM DETECTION; WEB CRAWLERS;

EID: 84857554841     PISSN: 18650929     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-25206-8_21     Document Type: Conference Paper
Times cited : (10)

References (18)
  • 1
  • 2
    • 78650024410 scopus 로고    scopus 로고
    • Pear Analytics: Twitter study (2009), http://www.pearanalytics.com/wp- content/uploads/2009/08/Twitter-Study-August-2009.pdf
    • (2009) Twitter Study
  • 13
    • 77958488685 scopus 로고    scopus 로고
    • Detecting Spam Bots in Online Social Networking Websites: A Machine Learning Approach
    • Foresti, S., Jajodia, S. (eds.) Data and Applications Security and Privacy XXIV. Springer, Heidelberg
    • Wang, A.H.: Detecting Spam Bots in Online Social Networking Websites: A Machine Learning Approach. In: Foresti, S., Jajodia, S. (eds.) Data and Applications Security and Privacy XXIV. LNCS, vol. 6166, pp. 335-342. Springer, Heidelberg (2010)
    • (2010) LNCS , vol.6166 , pp. 335-342
    • Wang, A.H.1
  • 16
    • 78649999189 scopus 로고    scopus 로고
    • Twitter: The twitter rules (2009), http://help.twitter.com/forums/26257/ entries/18311
    • (2009) The Twitter Rules
  • 17
    • 0001116877 scopus 로고
    • Binary codes capable of correcting deletions, insertions and reversals
    • Levenshtein, V.I.: Binary codes capable of correcting deletions, insertions and reversals. Soviet Physics Doklady 10, 707-710 (1966)
    • (1966) Soviet Physics Doklady , vol.10 , pp. 707-710
    • Levenshtein, V.I.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.