Open Access   Article Go Back

An Investigation on Social Media Issues Using Big Data Analytics

K. Yemunarane1 , D. Hemavathi2

Section:Survey Paper, Product Type: Journal Paper
Volume-06 , Issue-08 , Page no. 5-8, Oct-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6si8.58

Online published on Oct 31, 2018

Copyright © K. Yemunarane, D. Hemavathi . 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.

View this paper at   Google Scholar | DPI Digital Library

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: K. Yemunarane, D. Hemavathi, “An Investigation on Social Media Issues Using Big Data Analytics,” International Journal of Computer Sciences and Engineering, Vol.06, Issue.08, pp.5-8, 2018.

MLA Style Citation: K. Yemunarane, D. Hemavathi "An Investigation on Social Media Issues Using Big Data Analytics." International Journal of Computer Sciences and Engineering 06.08 (2018): 5-8.

APA Style Citation: K. Yemunarane, D. Hemavathi, (2018). An Investigation on Social Media Issues Using Big Data Analytics. International Journal of Computer Sciences and Engineering, 06(08), 5-8.

BibTex Style Citation:
@article{Yemunarane_2018,
author = {K. Yemunarane, D. Hemavathi},
title = {An Investigation on Social Media Issues Using Big Data Analytics},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {10 2018},
volume = {06},
Issue = {08},
month = {10},
year = {2018},
issn = {2347-2693},
pages = {5-8},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=465},
doi = {https://doi.org/10.26438/ijcse/v6i8.58}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i8.58}
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=465
TI - An Investigation on Social Media Issues Using Big Data Analytics
T2 - International Journal of Computer Sciences and Engineering
AU - K. Yemunarane, D. Hemavathi
PY - 2018
DA - 2018/10/31
PB - IJCSE, Indore, INDIA
SP - 5-8
IS - 08
VL - 06
SN - 2347-2693
ER -

           

Abstract

This paper describes how big data technologies are converging to offer a cost-effective delivery model social media based big data analytics. Social Media is a powerful technology to perform massive-scale and complex computing. It eliminates the need to maintain expensive computing hardware, dedicated space, and software. Massive growth in the scale of data or big data generated through social media has been observed. Addressing big data is a challenging and time demanding task that requires a large computational infrastructure to ensure successful data processing and analysis. In this paper the relationship between big data and social media, the classification of big data and the scope of big data analytics are discussed.

Key-Words / Index Term

Big Data, Social Media, Techniques, Big Data Analytics, Clustering

References

[1] D.Aruna Kumari , Dr.K.Rajasekhar rao, M.suman “ Privacy preserving distributed data mining using steganography “In Procc. Of CNSA-2010, Springer Libyary
[2] T.Anuradha, suman M,Aruna Kumari D “Data obscuration in privacy preserving data mining in Procc International conference on web sciences ICWS 2009.
[3] Agrawal, R. & Srikant, R.(2000). Privacy Preserving Data Mining. In Proc. of ACM SIGMOD Conference on Management of Data (SIGMOD’00), Dallas, TX.
[4] Alexandre Evfimievski, Tyrone Grandison Privacy Preserving Data Mining. IBM Almaden Research Center 650 Harry Road, San Jose, California 95120, USA
[5] Agarwal Charu C., Yu Philip S., Privacy Preserving Data Mining: Models and Algorithms, New York, Springer, 2008.
[6] Oliveira S.R.M, Zaiane Osmar R., A Privacy-Preserving Clustering Approach Toward Secure and Effective Data Analysis for Business Collaboration, In Proceedings of the International Workshop on
Privacy and Security Aspects of Data Mining in conjunction with ICDM 2004, Brighton, UK, November 2004.
[7] Flavius L. Gorgônio and José Alfredo F. Costa“Privacy-Preserving Clustering on Distributed Databases:A Review and Some Contributions
[8] D.Aruna Kumari, Dr.K.rajasekhar rao,M.Suman “Privacy preserving distributed data mining: a new approach for detecting network traffic using steganography” in international journal of systems and technology(IJST) june 2011.
[9] Binit kumar Sinha “Privacy preserving, and C. S. Yang, A Fast VQ Codebook Generation Algorithm via Pattern Reduction, Pattern Recognition Letters, vol. 30, pp. 653{660, 2009}
[10] C. W. Tsai, C. Y. Lee, M. C. Chiang Kurt Thearling, Information about data mining and analytic technologies http://www.thearling.com/
[11] K.Somasundaram, S.Vimala,“A Novel Codebook Initialization Technique for Generalized Lloyd Algorithm using Cluster Density”, International Journal on Computer Science and Engineering, Vol. 2, No. 5, pp. 1807-1809, 2010.
[12] K.Somasundaram, S.Vimala, “Codebook Generation for Vector Quantization with Edge Features”, CiiT International Journal of Digital Image Processing, Vol. 2, No.7, pp. 194-198, 2010.
[13] Vassilios S. Verykios, Elisa Bertino, Igor Nai Fovino State-of-the-art in Privacy Preserving Data Mining in SIGMOD Record, Vol. 33, No. 1, March 2004.
[14] Quantization: A Review”, IEEE Transactions on Communications, Vol. 36, No. 8, August 1988.
[15] Berger T, “Rate Distortion Theory”, Englewood Cliffs, Prentice-Hall,NJ, 1971.
[16] A.Gersho and V.Cuperman, “Vector Quantization: APattern Matching Technique for Speech Coding”, IEEE Communications, Mag., pp 15-21, 1983.
[17] "Privacy Preserving Data Mining - IBM Research: Almaden: San Jose
[18] D.Aruna Kumari, Dr.K.Rajasekhara rao, M.suman “Privacy Preserving Clustering in DDM using Cryptography”in TJ-RJCSE-IJ-06.