Abstract
Twitter is a microblogging service allowing users to post up to 280 characters at a time describing their thoughts. Twitter currently receives about 500 million tweets a day, in which people share their comments regarding a wide range of topics. In the process of creating social network profiles, users reveal a lot about themselves in what they share and how they say it. Through self-description, status update, and tweets, we can find a lot about the users. A user’s knowledge of social sites could be remarkably improved if other information like demographic attributes and user’s personal interest and the interest of other users are considered. This is truer in case of celebrity users. This chapter attempts to analyze celebrity tweets to provide relevant recommendations to the practitioners. The tweets of celebrity users are classified using two distinct approaches (1) Fixed Classification into six predefined categories and (2) Generating a category if the tweet does not belong to any defined category. The first kind of classification has been done in three different ways; by individually applying Naïve Bayes, Decision Tree, and Support Vector Machine. For generating a new category, Latent Dirichlet Allocation is used. Henceforth, this Persona Classification of Celebrity Twitter Users will help users to gain insight into their interests thereby decluttering their twitter feed and showing them relevant content on their feed. With the understanding of celebrity persona, smart recommendation systems can also be designed.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Agnihotri, A., & Bhattacharya, S. (2016). Celebrity endorsement and market valuation: Evidence from India. In Celebrating America’s pastimes: Baseball, hot dogs, apple pie and marketing? (pp. 709–713). Cham: Springer.
AlAlwan, A., Rana, N. P., Dwivedi, Y. K., & Algharabat, R. (2017). Social media in marketing: A review and analysis of the existing literature. Telematics and Informatics, 34(7), 1177–1190.
Armstrong, G. M., Jr. (1990). The reification of celebrity: Persona as property. Louisiana Law Review, 51, 443.
Balasubramanian, P., Gopal, A. V., & Reefana, S. (2016). A case study on misleading celebrity endorsements and its impact on consumer behavior. Bonfring International Journal of Industrial Engineering and Management Science, 6(3), 93–95.
Byrne, A., Whitehead, M., & Breen, S. (2003). The naked truth of celebrity endorsement. British Food Journal, 105(4/5), 288–296.
Chen, Q., Yao, L., & Yang, J. (2016). Short text classification based on LDA topic model. In 2016 International Conference on Audio, Language and Image Processing (ICALIP) (pp. 749–753). Washington: IEEE.
Davies, F., & Slater, S. (2015). Sport celebrity endorsement and the British consumer. In Marketing dynamism & sustainability: Things change, things stay the same… (pp. 191–191). Cham: Springer.
Dixon, H., Scully, M., Niven, P., Kelly, B., Chapman, K., & Donovan, R. (2014). Effects of nutrient content claims, sports celebrity endorsements and premium offers on pre-adolescent children’s food preferences: Experimental research. Paediatric Obesity, 9(2).
Drake, P., & Higgins, M. (2006). I’ma celebrity, get me into politics. In S. Holmes & S. Redmond (Eds.), Framing celebrity: New directions in celebrity culture (pp. 87–100). London: Routledge.
Dwivedi, Y. K., Kapoor, K. K., & Chen, H. (2015). Social media marketing and advertising. The Marketing Review, 15(3), 289–309.
Dyer, R. (2013). Heavenly bodies: Film stars and society. New York: Routledge.
Elberrichi, Z., Rahmoun, A., & Bentaalah, M. A. (2008). Using WordNet for text categorization. International Arab Journal of Information Technology (IAJIT), 5(1).
Felix, R., & Borges, A. (2014). Celebrity endorser attractiveness, visual attention, and implications for ad attitudes and brand evaluations: A replication and extension. Journal of Brand Management, 21(7-8), 579–593.
Fraley, C., & Raftery, A. E. (2006). MCLUST version 3: An R package for normal mixture modeling and model-based clustering. Washington: Washington University Seattle Department of Statistics.
Go, A., Bhayani, R., & Huang, L. (2009). Twitter sentiment classification using distant supervision. CS224N Project Report, Stanford (Vol. 1, issue 12).
Golbeck, J., Robles, C., Edmondson, M., & Turner, K. (2011). Predicting personality from twitter. In Privacy, Security, Risk and Trust (PASSAT) and 2011 IEEE Third International Conference on Social Computing (SocialCom) (pp. 149–156). Washington: IEEE.
Heider, F. (1946). Attitudes and cognitive organization. The Journal of Psychology, 21(1), 107–112.
Jiang, J., Huang, Y. H., Wu, F., Choy, H. Y., & Lin, D. (2015). At the crossroads of inclusion and distance: Organizational crisis communication during celebrity-endorsement crises in China. Public Relations Review, 41(1), 50–63.
Kapoor, K. K., Tamilmani, K., Rana, N. P., Patil, P., Dwivedi, Y. K., & Nerur, S. (2018). Advances in social media research: Past, present and future. Information Systems Frontiers., 20(3), 531–558.
Kilburn, D. (1998). Star power. Adweek Eastern Edition, 39(2), 20–21.
Kotler, P., Rein, I. J., & Stoller, M. R. (1987). High visibility. New York: Dodd, Mead & Company.
Lehmann, J., Gonçalves, B., Ramasco, J. J., & Cattuto, C. (2012). Dynamical classes of collective attention in twitter. In Proceedings of the 21st International Conference on World Wide Web (pp. 251–260). New York: ACM.
Leiss, W., Kline, S., & Jhally, S. (1990). Social communication in advertising: Persons, products & images of well-being. New York: Psychology Press.
Marshall, P. D. (2010). The promotion and presentation of the self: Celebrity as marker of presentational media. Celebrity Studies, 1(1), 35–48.
Marwick, A., & Boyd, D. (2011). To see and be seen: Celebrity practice on Twitter. Convergence, 17(2), 139–158.
McCracken, G. (1989). Who is the celebrity endorser? Cultural foundations of the endorsement process. Journal of consumer research, 16(3), 310–321.
Meyers, E. (2009). “Can you handle my truth?”: Authenticity and the celebrity star image. The Journal of Popular Culture, 42(5), 890–907.
Njuguna, S. P., & Otieno, H. N. (2015). Influence of celebrity endorsements on young consumers’ brand recall behaviour in Kenya: A case of Nairobi County.
Rindova, V. P., Pollock, T. G., & Hayward, M. L. (2006). Celebrity firms: The social construction of market popularity. Academy of Management Review, 31(1), 50–71.
Sakaki, T., Okazaki, M., & Matsuo, Y. (2010). Earthquake shakes Twitter users: Real-time event detection by social sensors. In Proceedings of the 19th International Conference on World Wide Web (pp. 851–860). New York: ACM.
Shareef, M. A., Mukerji, B., Dwivedi, Y. K., Rana, N. P., & Islam, R. (2019). Social media marketing: Comparative effect of advertisement sources. Journal of Retailing and Consumer Services, 46, 58–69.
Shiau, W.-L., Dwivedi, Y. K., & Yang, H.-S. (2017). Co-citation and cluster analyses of extant literature on social networks. International Journal of Information Management, 37(5), 390–399.
Siolas, G., & d’Alché-Buc, F. (2000). Support vector machines based on a semantic kernel for text categorization. In Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on IEEE (Vol. 5, pp. 205–209). Washington: IEEE.
Sriram, B., Fuhry, D., Demir, E., Ferhatosmanoglu, H., & Demirbas, M. (2010). Short text classification in twitter to improve information filtering. In Proceedings of the 33rd international ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 841–842). New York: ACM.
Stephens, A., & Rice, A. (1998). Spicing up the message. Finance Week, 76(26), 46–47.
Trope, Y., & Liberman, N. (2000). Temporal construal and time-dependent changes in preference. Journal of Personality and Social Psychology, 79(6), 876.
Ugheoke, T. O., & Saskatchewan, R. (2014). Detecting the gender of a tweet sender. M.Sc. Project report, Department of Computer Science, University of Regina, Regina.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Kaul, A., Mittal, V., Chaudhary, M., Arora, A. (2020). Persona Classification of Celebrity Twitter Users. In: Rana, N.P., et al. Digital and Social Media Marketing. Advances in Theory and Practice of Emerging Markets. Springer, Cham. https://doi.org/10.1007/978-3-030-24374-6_8
Download citation
DOI: https://doi.org/10.1007/978-3-030-24374-6_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-24373-9
Online ISBN: 978-3-030-24374-6
eBook Packages: Business and ManagementBusiness and Management (R0)