Human Being Character Analysis from Their Social Networking Profiles

Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2016, Vol 18, Issue 3

Abstract

In this paper, characteristics of human beings obtained from profile statement present in their social networking profile status are analyzed in terms of introvert, extrovert or ambivert. Recently, Machine learning plays a vital role in classifying the human characteristics. The user profile status is collected from LinkedIn, a popular professional social networking application. Oauth2.0 protocol is used for login into the LinkedIn and web scrapping using JavaScript is used for information extraction of the registered users. Then, Word Net: a lexical database is used for forming the word clusters such as: extrovert and introvert using semi-supervisedlearning techniques. K-nearest neighbor classification algorithm is finally considered for classifying the profiles into various available categories. The results obtained in the proposed method are encouraging with good accuracy

Authors and Affiliations

Biswaranjan Samal , ,Mrutyunjaya Panda

Keywords

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  • EP ID EP90668
  • DOI -
  • Views 127
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How To Cite

Biswaranjan Samal, , Mrutyunjaya Panda (2016).  Human Being Character Analysis from Their Social Networking Profiles. IOSR Journals (IOSR Journal of Computer Engineering), 18(3), 44-52. https://europub.co.uk/articles/-A-90668