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Implementing Big Data Analytics Through Network Analysis Software Applications in Strategizing Higher Learning Institutions

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Big Data Processing Using Spark in Cloud

Part of the book series: Studies in Big Data ((SBD,volume 43 ))

Abstract

With the growth and large-scale usage of social networks in the dissemination of knowledge in Higher education Institutions, a need is being increasingly felt to tame and utilize this vast (read Big) data for a more worldly use. With the use of various NASA (Network Analysis Software Applications) Tools, this aim can be easily achieved. NASA can be applied to various online social media networks generated data sets used by Educational Institutions like Twitter, Linked, or Proprietary Institution specific platforms for predicting and formulating student specific academic, safe-campus, and business strategies. As widely known, the above-listed social media (SM) applications help us in sharing digital artifacts (antiques) and capturing digital footprints. The common utility among these social media applications is that they are able to create natural network data. These OSMNs (online social media networks) represent the links or relationships between content generators as they look, react, comment, or link to one another’s content. There are many forms of computer-mediated social interaction which includes SMS messages, emails, discussion groups, blogs, wikis, videos, and photo sharing systems, chat rooms, and “social network services”. All these applications generate social media datasets of social friendships. Thus OSMNs have academic and pragmatic value and can be leveraged to illustrate the crucial contributors and the content. Our study takes all the above into account and thus shall explore the various Network Analysis Software Applications to study the practical aspects of big data analytics that can be used to better strategies Higher learning Institutions.

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Notes

  1. 1.

    www.facebook.com: Very famous social networking site.

  2. 2.

    www.twitter.com: Social networking site.

  3. 3.

    https://gephi.org: Social network analysis tool.

  4. 4.

    http://www.smrfoundation.org/nodexl/: Microsoft Excel add-in for social network analysis.

  5. 5.

    Pajek vlado.fmf.uni-lj.si/pub/networks/pajek: Social network analysis tool.

  6. 6.

    www.myspace.com: Social network interactive site.

  7. 7.

    NETVIZZ: Tool used to analyze Facebook data.

  8. 8.

    IGraph.sourceforge.net.

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Authors and Affiliations

  1. VIPS, GGSIPU, New Delhi, India

    Meenu Chopra & Cosmena Mahapatra

Authors
  1. Meenu Chopra
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  2. Cosmena Mahapatra
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Corresponding author

Correspondence to Meenu Chopra .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, GB Pant Government Engineering College, New Delhi, India

    Mamta Mittal

  2. Department of Automation and Applied Informatics, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina E. Balas

  3. Department of Computer Science and Engineering, Bharati Vidyapeeth’s College of Engineering, New Delhi, India

    Lalit Mohan Goyal

  4. Department of Computer Science and Engineering, Laxmi Narayan College of Technology, Jabalpur, Madhya Pradesh, India

    Raghvendra Kumar

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Chopra, M., Mahapatra, C. (2019). Implementing Big Data Analytics Through Network Analysis Software Applications in Strategizing Higher Learning Institutions. In: Mittal, M., Balas, V., Goyal, L., Kumar, R. (eds) Big Data Processing Using Spark in Cloud. Studies in Big Data, vol 43 . Springer, Singapore. https://doi.org/10.1007/978-981-13-0550-4_6

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  • DOI: https://doi.org/10.1007/978-981-13-0550-4_6

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-0549-8

  • Online ISBN: 978-981-13-0550-4

  • eBook Packages: EngineeringEngineering (R0)

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