Understanding the Users Personal Attributes Similarity Across Online Social Networks
Waseem Ahmad1, Rashid Ali2
1Waseem Ahmad, Department of Computer Engineering, ZHCET, AMU, Aligarh, India.
2Rashid Ali, Department of Computer Engineering, ZHCET, AMU, Aligarh, India.
Manuscript received on 27 August 2019. | Revised Manuscript received on 07 September 2019. | Manuscript published on 30 September 2019. | PP: 3902-3908 | Volume-8 Issue-11, September 2019. | Retrieval Number: K12970981119/2019©BEIESP | DOI: 10.35940/ijitee.K1297.0981119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this modern era of technology, everyone accessing the Internet is obsessed with social media. A User accesses different social media services to fulfill his diverse needs. For instance, Instagram is mainly used for sharing personal visual content while Twitter is known for finding latest news and trends, similarly Facebook for personal posts. Such services lead to the distribution of personal information of an Internet user on these platforms. In this paper, we build a framework to discover the relationship among the attributes of a user across the social media.We use different fuzzy string matching algorithms to find the similarities between the attributes. We extract the ‘name’ and ‘username’ from a publicly shared dataset and apply two character based and token based algorithms on these features. The results are indicative of the fact that only a limited number of users share the same name and username across the sites. On further analysis, it is found that although name and username of most of the users do not exactly match, they tend to be similar with the infinitesimal difference like; underscore, period, one digit numbers, etc. This study provides an analysis of the typical variations in names and usernames, which can further be studied for the extension to other social networks This profile will help in behavior analysis of a user, which will further help us to improve recommendations and analyze for criminal behavior and similar applications.
Keywords: Personal Information, Social Account, User Identity, Cross link posts.
Scope of the Article: Social Networks