SPAM DETECTION IN SOCIAL NETWORKS USING ENSEMBLE LEARNING

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Kavousi Mohammad Mahdi; Rezvanian Alireza

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Seminar Paper

Paper Information

Seminar: INTERNATIONAL CONFERENCE ON WEB RESEARCH
Year:2019 | Issue:5

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Title

SPAM DETECTION IN SOCIAL NETWORKS USING ENSEMBLE LEARNING

Author(s)

Kavousi Mohammad Mahdi | Rezvanian Alireza

Keywords

SOCIAL NETWORK ANALYSIS

SPAM DETECTION

DATA MINING

MACHINE LEARNING

ENSEMBLE LEARNING

Abstract

TODAY, SOCIAL NETWORKS HAVE PROVIDED A SUITABLE PLATFORM FOR SOCIAL RELATIONSHIP. AMONG ONLINE SOCIAL NETWORKS, TWITTER HAS BECOME A POPULAR PLATFORM FOR INFORMATION DIFFUSION AROUND THE WORLD. DUE TO POPULARITY OF TWITTER, IT HAS BEEN TARGETED BY SPAMMERS AND MALICIOUS ACTIVITIES. IN THIS REGARD, SEVERAL STUDIES HAVE BEEN CONDUCTED USING MACHINE LEARNING TECHNIQUES BY RESEARCHERS TO REACH PROMISING RESULTS. IN RECENT YEARS, ENSEMBLE LEARNING ALGORITHMS HAVE BEEN PRESENTED AS ONE OF THE MODERN MACHINE LEARNING TECHNIQUES, DUE TO ITS HIGH ACCURACY, FOR DATA MINING. IN THIS PAPER, WE PROPOSE A DATA MINING FRAMEWORK USING ENSEMBLE LEARNING FOR SPAM DETECTION IN TWITTER. IN THE PROPOSED METHOD, AFTER DATA COLLECTION, PREPROCESSING, FEATURE EXTRACTION AND FEATURE SELECTION, THE CLASSIFICATION IS CONDUCTED BY ENSEMBLE LEARNING USING THE DECISION TREE, K-NEAREST NEIGHBOR AND NAï VE BAYES. THE SIMULATION RESULTS ARE COMPARED WITH OTHER CLASSIFICATION ALGORITHMS.

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APA: Copy

Kavousi, Mohammad Mahdi, & Rezvanian, Alireza. (2019). SPAM DETECTION IN SOCIAL NETWORKS USING ENSEMBLE LEARNING. INTERNATIONAL CONFERENCE ON WEB RESEARCH. SID. https://sid.ir/paper/949135/en

Vancouver: Copy

Kavousi Mohammad Mahdi, Rezvanian Alireza. SPAM DETECTION IN SOCIAL NETWORKS USING ENSEMBLE LEARNING. 2019. Available from: https://sid.ir/paper/949135/en

IEEE: Copy

Mohammad Mahdi Kavousi, and Alireza Rezvanian, “SPAM DETECTION IN SOCIAL NETWORKS USING ENSEMBLE LEARNING,” presented at the INTERNATIONAL CONFERENCE ON WEB RESEARCH. 2019, [Online]. Available: https://sid.ir/paper/949135/en

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