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Abnormal Facebook Multimedia Detection on Facebook using IQR Method

Siddu P Algur1 , Suraj Jain2 , Prashant Bhat3

  1. Dept. of Computer Science, Rani Channamma University, Belagavi, India.
  2. JSS Shri Manjunatheshwara Institute of UG and PG Studies, Dharwad, India.
  3. Dept. of Business and Data Analytics, Christ Institute of Management, Pune, India.

Correspondence should be addressed to: prashantrcu@gmail.com .

Section:Research Paper, Product Type: Journal Paper
Volume-5 , Issue-8 , Page no. 141-146, Aug-2017

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v5i8.141146

Online published on Aug 30, 2017

Copyright © Siddu P Algur, Suraj Jain, Prashant Bhat . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Siddu P Algur, Suraj Jain, Prashant Bhat, “Abnormal Facebook Multimedia Detection on Facebook using IQR Method,” International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.141-146, 2017.

MLA Style Citation: Siddu P Algur, Suraj Jain, Prashant Bhat "Abnormal Facebook Multimedia Detection on Facebook using IQR Method." International Journal of Computer Sciences and Engineering 5.8 (2017): 141-146.

APA Style Citation: Siddu P Algur, Suraj Jain, Prashant Bhat, (2017). Abnormal Facebook Multimedia Detection on Facebook using IQR Method. International Journal of Computer Sciences and Engineering, 5(8), 141-146.

BibTex Style Citation:
@article{Algur_2017,
author = {Siddu P Algur, Suraj Jain, Prashant Bhat},
title = {Abnormal Facebook Multimedia Detection on Facebook using IQR Method},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {8 2017},
volume = {5},
Issue = {8},
month = {8},
year = {2017},
issn = {2347-2693},
pages = {141-146},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1403},
doi = {https://doi.org/10.26438/ijcse/v5i8.141146}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v5i8.141146}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1403
TI - Abnormal Facebook Multimedia Detection on Facebook using IQR Method
T2 - International Journal of Computer Sciences and Engineering
AU - Siddu P Algur, Suraj Jain, Prashant Bhat
PY - 2017
DA - 2017/08/30
PB - IJCSE, Indore, INDIA
SP - 141-146
IS - 8
VL - 5
SN - 2347-2693
ER -

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Abstract

Recently, discovering outliers among large scale Facebook multimedia have attracted attention of many Facebook mining researchers. There are number of outlier multimedia exists in each category of Facebook multimedia such as- ‘Entertainment’, ‘Sports’, ‘News and Politics’, etc. The task of identifying and manipulate (to remove from the Facebook or to share with others in the Facebook, or to watch/download from the Facebook etc.) such outlier Facebook multimedia have gained significant important research aspect in the area of Facebook Mining Research. In this work, we propose a novel method to detect outliers from the Facebook multimedia based on their metadata objects. Large scale Facebook multimedia metadata objects such as- length, view counts, numbers of comments, rating information are considered for outliers’ detection process. The outlier detection method–Inter-Quartile Range (IQR) is used to find outlier Facebook multimedia of same age. The resultant outliers are analysed and compared as a step in the process of knowledge discovery.

Key-Words / Index Term

Outliers, Inter-Quartile Range, Facebook Multimedia Outliers, Facebook, Metadata

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