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Title: :  Survey Paper on Detecting Unknown or Fake User Accounts on Different Microblogging and Social Media Networks
PaperId: :  3410
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 2 Issue 6 2016
DUI:    16.0415/IJARIIE-3410
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Darshan BiyaniSKN-SITS, LONAVALA
Balaji LaseSKN-SITS, LONAVALA
Sagar SawarkarSKN-SITS, LONAVALA
Vaibhav UmaleSKN-SITS, LONAVALA

Abstract

Information Technology
Cross-Platform, Social Media Network, Anonymous Identical Users, Friend Relationship, User Identification
The last few years have witnessed the emergence and evolution of a vibrant research stream on a large variety of online Social Media Network (SMN) platforms. Recognizing anonymous, yet identical users among multiple SMNs is still an intractable problem. Clearly, cross-platform exploration may help solve many problems in social computing in both theory and applications. Since public profiles can be duplicated and easily impersonated by users with different purposes, most current user identification resolutions, which mainly focus on text mining of users’ public profiles, are fragile. Some studies have attempted to match users based on the location and timing of user content as well as writing style. However, the locations are sparse in the majority of SMNs, and writing style is difficult to discern from the short sentences of leading SMNs such as S in a Microblog and Twitter. Moreover, since online SMNs are quite symmetric, existing user identification schemes based on network structure are not effective. The real-world friend cycle is highly individual and virtually no two users share a congruent friend cycle. Therefore, it is more accurate to use a friendship structure to analyse cross-platform SMNs. Since identical users tend to set up partial similar friendship structures in different SMNs, we proposed the Friend Relationship-Based User Identification (FRUI) algorithm. FRUI calculates a match degree for all candidate User Matched Pairs (UMPs), and only UMPs with top ranks are considered as identical users. We also developed two propositions to improve the efficiency of the algorithm. Results of extensive experiments demonstrate that FRUI performs much better than current network structure-based algorithms.

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IJARIIE Darshan Biyani, Balaji Lase, Sagar Sawarkar, and Vaibhav Umale. "Survey Paper on Detecting Unknown or Fake User Accounts on Different Microblogging and Social Media Networks" International Journal Of Advance Research And Innovative Ideas In Education Volume 2 Issue 6 2016 Page 869-873
MLA Darshan Biyani, Balaji Lase, Sagar Sawarkar, and Vaibhav Umale. "Survey Paper on Detecting Unknown or Fake User Accounts on Different Microblogging and Social Media Networks." International Journal Of Advance Research And Innovative Ideas In Education 2.6(2016) : 869-873.
APA Darshan Biyani, Balaji Lase, Sagar Sawarkar, & Vaibhav Umale. (2016). Survey Paper on Detecting Unknown or Fake User Accounts on Different Microblogging and Social Media Networks. International Journal Of Advance Research And Innovative Ideas In Education, 2(6), 869-873.
Chicago Darshan Biyani, Balaji Lase, Sagar Sawarkar, and Vaibhav Umale. "Survey Paper on Detecting Unknown or Fake User Accounts on Different Microblogging and Social Media Networks." International Journal Of Advance Research And Innovative Ideas In Education 2, no. 6 (2016) : 869-873.
Oxford Darshan Biyani, Balaji Lase, Sagar Sawarkar, and Vaibhav Umale. 'Survey Paper on Detecting Unknown or Fake User Accounts on Different Microblogging and Social Media Networks', International Journal Of Advance Research And Innovative Ideas In Education, vol. 2, no. 6, 2016, p. 869-873. Available from IJARIIE, http://ijariie.com/AdminUploadPdf/Survey_Paper_on_Detecting_Unknown_or_Fake_User_Accounts_on_Different_Microblogging_and_Social_Media_Networks_ijariie3410.pdf (Accessed : ).
Harvard Darshan Biyani, Balaji Lase, Sagar Sawarkar, and Vaibhav Umale. (2016) 'Survey Paper on Detecting Unknown or Fake User Accounts on Different Microblogging and Social Media Networks', International Journal Of Advance Research And Innovative Ideas In Education, 2(6), pp. 869-873IJARIIE [Online]. Available at: http://ijariie.com/AdminUploadPdf/Survey_Paper_on_Detecting_Unknown_or_Fake_User_Accounts_on_Different_Microblogging_and_Social_Media_Networks_ijariie3410.pdf (Accessed : )
IEEE Darshan Biyani, Balaji Lase, Sagar Sawarkar, and Vaibhav Umale, "Survey Paper on Detecting Unknown or Fake User Accounts on Different Microblogging and Social Media Networks," International Journal Of Advance Research And Innovative Ideas In Education, vol. 2, no. 6, pp. 869-873, Nov-Dec 2016. [Online]. Available: http://ijariie.com/AdminUploadPdf/Survey_Paper_on_Detecting_Unknown_or_Fake_User_Accounts_on_Different_Microblogging_and_Social_Media_Networks_ijariie3410.pdf [Accessed : ].
Turabian Darshan Biyani, Balaji Lase, Sagar Sawarkar, and Vaibhav Umale. "Survey Paper on Detecting Unknown or Fake User Accounts on Different Microblogging and Social Media Networks." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 2 number 6 ().
Vancouver Darshan Biyani, Balaji Lase, Sagar Sawarkar, and Vaibhav Umale. Survey Paper on Detecting Unknown or Fake User Accounts on Different Microblogging and Social Media Networks. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2016 [Cited : ]; 2(6) : 869-873. Available from: http://ijariie.com/AdminUploadPdf/Survey_Paper_on_Detecting_Unknown_or_Fake_User_Accounts_on_Different_Microblogging_and_Social_Media_Networks_ijariie3410.pdf
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