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A Brief Review on Impact of Social Network Mining on Online Shopping for Classifying Customers

S.K. Mishra1 , A. Agarwal2

Section:Review Paper, Product Type: Journal Paper
Volume-7 , Issue-7 , Page no. 87-92, Jul-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i7.8792

Online published on Jul 31, 2019

Copyright © S.K. Mishra, A. Agarwal . 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: S.K. Mishra, A. Agarwal, “A Brief Review on Impact of Social Network Mining on Online Shopping for Classifying Customers,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.7, pp.87-92, 2019.

MLA Style Citation: S.K. Mishra, A. Agarwal "A Brief Review on Impact of Social Network Mining on Online Shopping for Classifying Customers." International Journal of Computer Sciences and Engineering 7.7 (2019): 87-92.

APA Style Citation: S.K. Mishra, A. Agarwal, (2019). A Brief Review on Impact of Social Network Mining on Online Shopping for Classifying Customers. International Journal of Computer Sciences and Engineering, 7(7), 87-92.

BibTex Style Citation:
@article{Mishra_2019,
author = {S.K. Mishra, A. Agarwal},
title = {A Brief Review on Impact of Social Network Mining on Online Shopping for Classifying Customers},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2019},
volume = {7},
Issue = {7},
month = {7},
year = {2019},
issn = {2347-2693},
pages = {87-92},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4726},
doi = {https://doi.org/10.26438/ijcse/v7i7.8792}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i7.8792}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4726
TI - A Brief Review on Impact of Social Network Mining on Online Shopping for Classifying Customers
T2 - International Journal of Computer Sciences and Engineering
AU - S.K. Mishra, A. Agarwal
PY - 2019
DA - 2019/07/31
PB - IJCSE, Indore, INDIA
SP - 87-92
IS - 7
VL - 7
SN - 2347-2693
ER -

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Abstract

Communication is the only way to exchange views and feelings. If communication between two parties is strong, there must always be more trust and decisions are taken firmly. Social networking sites are the potential tools which are utilized for communication without much physical efforts. Nowadays, the Social Networking phenomenon is spread over the globe and affects every individual who uses a social medium to communicate with others. Social networking sites have revolutionized the way companies communicate with their customers. The reachability of companies to customers has drastically improved because of the revolution in mobile technology. The main goal of our work is to get the insight into the impact of social networking on customer behavior, to explain why, when, and how social media has impacted on the customer decision process. We briefly introduce various laws used in mining techniques and the concept of link analyzis used for analyzing the data gathered from social networking sites. We explain the concept of centrality in social networks and exponential growth in online shopping and the causes behind this trend are also analyzed as well.

Key-Words / Index Term

Social Network Mining, E-commerce, Web Mining, Customer Behavior, Six Degree Separation

References

[1] Harris L, Rae A. Social networks: the future of marketing for small business. Journal of business strategy. 2009 Sep 4;30 (5):24-31.
[2] Watts DJ. The “new” science of networks. Annu. Rev. Sociol.. 2004 Aug 11;30:243-70.
[3] Odhiambo M, Adhiambo C. Social Media as a Tool of Marketing and Creating Brand awareness: Case study research.
[4] Irfan R, King CK, Grages D, Ewen S, Khan SU, Madani SA, Kolodziej J, Wang L, Chen D, Rayes A, Tziritas N. A survey on text mining in social networks. The Knowledge Engineering Review. 2015 Mar;30(2):157-70.
[5] Kanchan U, Kumar N, Gupta A. A study of online purchase behavior of customers in India. Ictact Journal on Management Studies. 2015;1(3).
[6] Salehan M, Kim D. Predicting the Performance of Online Consumer Reviews: A Sentiment Mining Approach.
[7] Alsubagh H. The impact of social networks on consumers` behaviors. International Journal of Business and Social Science. 2015 Jan 1;6(1).
[8] Verbeke W, Martens D, Baesens B. Social network analyzis for customer churn prediction. Applied Soft Computing. 2014 Jan 1;14:431-46.
[9] Wei GT, Kho S, Husain W, Zainol Z. A study of customer behavior through web mining. J Inform Sci Comput Technol. 2015 Feb;2(1):103-7.
[10] Watts DJ. Six degrees: The science of a connected age. WW Norton & Company; 2004 Feb 17.A
[11] Nohuddin PN, Christley R, Coenen F, Patel Y, Setzkorn C, Williams S. Social network trend analyzis using frequent pattern mining and self organizing maps. InInternational Conference on Innovative Techniques and Applications of Artificial Intelligence 2010 Dec 14 (pp. 311-324). Springer, London.
[12] Smith, P.R. and Zook, Z., 2012. Marketing communications: integrating offline and online with social media/PR Smith & Ze Zook. Philadelphia, PA: Kogan Page,.
[13] Kim, D., Kim, J.H. and Nam, Y., 2014. How does industry use social networking sites? An analyzis of corporate dialogic uses of Facebook, Twitter, YouTube, and LinkedIn by industry type. Quality & Quantity, 48(5), pp.2605-2614.
[14] Wang YY, Susarla A, Sambamurthy V. The untold story of social media on offline sales: the impact of Facebook in the US automobile industry.
[15] Ibrahim NF, Wang X, Bourne H. Exploring the effect of user engagement in online brand communities: Evidence from Twitter. Computers in Human Behavior. 2017 Jul 1;72:321-38.
[16] Wattenhofer, M., Wattenhofer, R. and Zhu, Z., 2012, May. The YouTube social network. In Sixth International AAAI Conference on Weblogs and Social Media.
[17] Koch, T., Gerber, C. and de Klerk, J.J., 2018. The impact of social media on recruitment: Are you LinkedIn?. SA Journal of Human Resource Management, 16(1), pp.1-14.
[18] http://www.smallbusinesssem.com/articles/marketing-on-flickr/2012
[19] Evans, N.J., Phua, J., Lim, J. and Jun, H., 2017. Disclosing Instagram influencer advertising: The effects of disclosure language on advertising recognition, attitudes, and behavioral intent. Journal of Interactive Advertising, 17(2), pp.138-149.
[20] Wang, R.J.H., Malthouse, E.C. and Krishnamurthi, L., 2015. On the go: How mobile shopping affects customer purchase behavior. Journal of Retailing, 91(2), pp.217-234.
[21] Kalia, P., Singh, T. and Kaur, N., 2016. An empirical study of online shoppers’ search behavior with respect to sources of information in Northern India. Productivity: A Quarterly Journal of the National Productivity Council, 56(4), pp.353-361.
[22] Grandhi S, Chugh R, Wibowo S. An Empirical Study of Customers’ Purchase Intentions from Australian Group Buying Sites.
[23] https://yourstory.com/2013/01/google-india-study-about-online-shopping
[24] Jeyashoke N, Vongterapak B, Long Y. Does Culture Matter? A Case Study on Online Retailing Stores across Three Asian Countries. InPACIS 2014 (p. 283).
[25] Khanna P, Sampat B. Factors influencing online shopping during Diwali festival 2014: Case study of Flipkart and Amazon. in. Journal of International Technology and Information Management. 2015;24(2):5.
[26] Mayfield, R., 2005. Social network dynamics and participatory politics. Extreme democracy, pp.116-132.
[27] Odlyzko, A. and Tilly, B., 2005. A refutation of Metcalfe’s Law and a better estimate for the value of networks and network interconnections. Manuscript, March, 2, p.2005.
[28] Zhang, X.Z., Liu, J.J. and Xu, Z.W., 2015. Tencent and Facebook data validate Metcalfe’s law. Journal of Computer Science and Technology, 30(2), pp.246-251.
[29] Centola D. The spread of behavior in an online social network experiment. science. 2010 Sep 3;329(5996):1194-7.
[30] Ghosh R, Lerman K. Predicting influential users in online social networks. arXiv preprint arXiv:1005.4882. 2010 May 26.