Big Data Social Media Analytics for Purchasing Behaviour

  • Authors

    • Shahid Shayaa
    • Ainin Sulaiman
    • Arsalan Zahid Piprani
    • Mohammed Ali Al-Garadi
    • Muhammad Ashraf
    2018-12-09
    https://doi.org/10.14419/ijet.v7i4.36.23917
  • Big data, Social media, Purchasing behavior, Sentiment analysis
  • The social media is rich in data and of late its data have been used for various types of analytics. This paper examines the purchasing behavior and sentiments of social media users from Jan - 2015 to Dec – 2016. The purchasing behaviour of the users is categorized into five: buy car, buy house, buy computer, buy hand phone and going for holiday. The paper will also demonstrate the trend of each individual category. The results of the analysis would provide businesses information on the social media users’ purchasing behavior, their sentiment thus allowing them to take more appropriate strategies to enhance their competitiveness.

     

     

  • References

    1. [1] D. Arora, K. F. Li and S. W. Neville. Consumers' sentiment analysis of popular phone brands and operating system preference using Twitter data: A feasibility study. Proceedings of the 29th IEEE International Conference of Advanced Information Networking and Applications, (2015) March 680-686; Taipei, Taiwan

      [2] Deep Analytics. Unstructured data: A big deal in big data. Available at: http://www.digitalreasoning.com/resources/Holistic-Analytics.pdf (Accessed 22-09-2016).

      [3] W. He, S. Zha and L. Li. Social media competitive analysis and text mining: A case study in the pizza industry. Intl J. of Info Mngt, 33(3), 464-472 (2013).

      [4] M. Hu and B. Liu. Mining and summarizing customer reviews. Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, (2004) August 168-177; Seattle, USA

      [5] Judith Hurwitz, Alan Nugent, Fern Halper, and Marcia Kaufman. Understanding Big Data for Dummies, http://www.dummies.com/how-to/content/ (Accessed 22-09-2016).

      [6] N.B. Lassen, R. Madsen and R. Vatrapu. Predicting iphone sales from iphone tweets. Proceedings of 18th IEEE International Conference on the Enterprise Distributed Object Computing (EDOC), (2014) September 81-90; Ulm, Germany

      [7] A. Semenov. Principles of social media monitoring and analysis software. Jyväskylä studies in computing. 168, 1456-5390 (2013)

      [8] M. Taboada, J. Brooke, M. Tofiloski, K. Voll, and M. Stede. Lexicon-based methods for sentiment analysis. Computational linguistics, 37(2), 267-307 (2011).

      [9] R. Thackeray, B. L. Neiger, C. L. Hanson, and J. F. McKenzie. Enhancing promotional strategies within social marketing programs: use of Web 2.0 social media. Health promotion practice. 9(4), 338-343 (2008).

      [10] A. Benlian, R. Titah, and T. Hess. Differential effects of provider recommendations and consumer reviews in E-commerce transactions: An experimental study. J. of Mngt Inf Sys. 29(1), 237-272 (2012).

      [11] L. Huang, C.-H. Tan, W. Ke, and K.-K. Wei. Comprehension and Assessment of Product Reviews: A Review-Product Congruity Proposition. J. of Mngt Info Sys. 30(3), 311-343 (2013).

      [12] E. Kouloumpis, T. Wilson, and J. D. Moore. Twitter sentiment analysis: The good the bad and the OMG! Proceedings of the 5th International AAAI Conference on Weblogs and Social Media, (2011) July 538-541; Barcelona, Spain.

      [13] A. Pak and P. Paroubek. Twitter as a corpus for sentiment analysis and opinion mining. Proceedings of the International Conference on Language Resources and Evaluation, (2010) May 17-23; Valletta, MaltaIn.

      [14] M. A. Al-garadi, K. D. Varathan, and S. D. Ravana. Cybercrime detection in online communications: The experimental case of cyberbullying detection in the Twitter network. Computers in Human Behavior. 63, 433-443 (2016).

      [15] M. A. Al-garadi, M. S. Khan, K. D. Varathan, G. Mujtaba, and A. M. Al-Kabsi. Using online social networks to track a pandemic: A systematic review. J. of Biomedical Informatics. 62, 1-11 (2016).

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  • How to Cite

    Shayaa, S., Sulaiman, A., Zahid Piprani, A., Ali Al-Garadi, M., & Ashraf, M. (2018). Big Data Social Media Analytics for Purchasing Behaviour. International Journal of Engineering & Technology, 7(4.36), 463-465. https://doi.org/10.14419/ijet.v7i4.36.23917