A Text Analysis Based Seamless Framework for Predicting Human Personality Traits from Social Networking Sites

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Ramya Sharada K 1,* Arti Arya 2 Ragini S 1 Harish Kumar 2 Abinaya G 3

1. ITC Infotech, Bangalore, Karnataka, India

2. PESIT, Bangalore South Campus, Karnataka, India

3. Wipro, Bangalore, Karnataka, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijitcs.2012.10.04

Received: 26 Dec. 2011 / Revised: 7 Apr. 2012 / Accepted: 23 Jun. 2012 / Published: 8 Sep. 2012

Index Terms

Clustering, Classification, Social Networking Sites, Text Summarization, Text Analysis


Predicting human behavior based on the usage of text on social networking sites can be a challenging area of interest to a particular community. Text mining being a major interest in Data Mining has vast applications in various fields. Clients can assess an individual’s behavior using the proposed framework that is based on person’s textual interaction with other people. In this paper, a framework is proposed for predicting human behavior in three phases- Text Extraction, Text cleaning and Text Analysis. For cleaning text, all the stop words have been removed and then the text is utilized for further processing. Then, the terms from the text are clustered based on semantic similarity and then gets associated with respective physiological parameters that identify a human behavior. This application is best suited for the fields of Criminal Sciences, Medical Sciences, Human Resource Department and Political Science and even for Matrimonial purposes. The proposed framework is applied on some famous world known celebrities and the results are quite encouraging.

Cite This Paper

Ramya Sharada K, Arti Arya, Ragini S, Harish Kumar, Abinaya G, "A Text Analysis Based Seamless Framework for Predicting Human Personality Traits from Social Networking Sites", International Journal of Information Technology and Computer Science(IJITCS), vol.4, no.10, pp.37-43, 2012. DOI:10.5815/ijitcs.2012.10.04


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