We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Reseach Article

A New Framework for Social Media Content Mining and Knowledge Discovery

by Prashant Bhat, Pradnya Malaganve, Prajna Hegde
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 36
Year of Publication: 2019
Authors: Prashant Bhat, Pradnya Malaganve, Prajna Hegde
10.5120/ijca2019918356

Prashant Bhat, Pradnya Malaganve, Prajna Hegde . A New Framework for Social Media Content Mining and Knowledge Discovery. International Journal of Computer Applications. 182, 36 ( Jan 2019), 17-20. DOI=10.5120/ijca2019918356

@article{ 10.5120/ijca2019918356,
author = { Prashant Bhat, Pradnya Malaganve, Prajna Hegde },
title = { A New Framework for Social Media Content Mining and Knowledge Discovery },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2019 },
volume = { 182 },
number = { 36 },
month = { Jan },
year = { 2019 },
issn = { 0975-8887 },
pages = { 17-20 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number36/30298-2019918356/ },
doi = { 10.5120/ijca2019918356 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:13:28.010574+05:30
%A Prashant Bhat
%A Pradnya Malaganve
%A Prajna Hegde
%T A New Framework for Social Media Content Mining and Knowledge Discovery
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 36
%P 17-20
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Social media has come up with many popular websites such as Facebook, Twitter, Instagram, LinkedIn etc for the use of the generation to share each other’s views. Social Media Content Mining is the process of extracting useful information i.e. Text, Video, Audio, Images from the Web by applying Data Mining techniques such as classification, clustering, regression, Outlier Detection and association rules etc can be applied to discover knowledge from web data. This paper presents some existing social media content mining techniques and proposed a new approach for efficient Data Mining frame work to extract useful knowledge from the web data.

References
  1. Christoph Trattner, Frank Kappe” Social stream marketing on Facebook: a case study”. International Journal of Social and Humanistic Computing · March 2013
  2. Niloofar Safi Samghabadi, Suraj Maharjan, Alan Sprague, Raquel Diaz-Spragu and Thamar Solorio ” Detecting Nastiness in Social Media”. Proceedings of the First Workshop on Abusive Language Online, pages 63–72, Vancouver, Canada, July 30 - August 4, 2017. Association for Computational Linguistics
  3. Gustavo Aguilar, Suraj Maharjan, A. Pastor L´opez-Monroy and Thamar Solorio “A Multi-task Approach for Named Entity Recognition in Social Media Data”. Proceedings of the 3rd Workshop on Noisy User-generated Text, pages 148–153 Copenhagen, Denmark, September 7, 2017. Association for Computational Linguistics
  4. Said A. Salloum , Mostafa Al-Emran and Khaled Shaalan “Mining Social Media Text: Extracting Knowledge from Facebook”. IJCDS Journal · March 2017
  5. Zahra Ashktorab, Christopher Brown, Manojit Nandi and Aron Culotta “Tweedr: Mining Twitter to Inform Disaster Response”. Proceedings of the 11th International ISCRAM Conference – University Park, Pennsylvania, USA, May 2014 S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih, eds.
  6. Cristobal Romero and Sebastian Ventura “Data mining in education” Volume 3, Januar y / Februar y 2013
  7. Umman Tugba Gursoy, Diren Bulut and Cemil Yigit “Social Media Mining and Sentiment Analysis for Brand Management”. Global Journal of Emerging Trends in e-Business, Marketing and Consumer Psychology (GJETeMCP) An Online International Research Journal (ISSN: 2311-3170) 2017 Vol: 3 Issue: 1
  8. Mashael Saeed Alqhtani, M. Rizwan Jameel Qureshi “Data Mining Approach For Classifying Twitter’s Users”. International Journal of Computer Engineering & Technology (IJCET) Volume 8, Issue 5, Sep-Oct 2017, pp. 42–53, Article ID: IJCET_08_05_006
  9. Saman Forouzandeh, Heirsh Soltanpanah and Amir Sheikhahmadi, “Content marketing through data mining on Facebook social network”. Volume 11, June 2014
  10. Siddu P. Algur, Prashant Bhat*, Suraj Jain, “The Role of Metadata in Web Video Mining: Issues and Perspectives.© International Journal of Engineering Sciences & Research Technology, 2015
  11. https://hackernoon.com/what-steps-should-one-take-while-doing-data-preprocessing-502c993e1caa
  12. https://www.lifewire.com/regression-1019655
  13. https://ieeexplore.ieee.org/document/4739542
  14. Thabit Zatari, “ Data Mining in Social Media”. International Journal of Scientific & Engineering Research, Volume 6, Issue 7, July-2015 152 ISSN 2229-5518
Index Terms

Computer Science
Information Sciences

Keywords

Data Mining Multimedia Data Classification Data Clustering Outlier Detection