Nur Sakinah Diyanah Abdullah
ABSTRACT
In this paper, we undertake sentiment analysis from netnography data to understand the need for giving special attention to sentiments expressed by the online crowd towards brand via the social media platform. The understanding of this will explain the emotions of the brand community subscribers towards the brand as the result of the interaction established with the brand online. This study utilizes a qualitative approach in which the input given by the brand community subscriber from three chosen social media platforms were analysed using AYLIEN, Text Analysis API and Monkeylearn software to extract sentiment polarities based on Positive, Negative, Sarcastic, Ideology and Neutral sentiments. The outcome shows that the provocation sentiment needs to be managed efficiently in order to trigger interaction within and between the online crowd and brand community subscribers for sustaining a long-term relationship over the social media platform for effective brand communication strategies.
- Ho, C. W., & Wang, Y. B. (2015). Re-purchase intentions and virtual customer relationships on social media brand community. Human-centric Computing and Information Sciences, 5--18.Google Scholar
- Bernoff, J. (2008), "2008 Forrester Groundswell Awards winners". Social Media Today. Retrieved from http://socialmediatoday.com/index.php?q 1/4 SMC/54276Google Scholar
- Noff, A. (2009), "Learning from Starbucks -- one tweet at a time". Retrieve from www.blonde20.com/blog/2009/11/19/learning-from-starbucks-one-tweet-at-a-time/Google Scholar
- West, T. (2012), "Starbucks tops social engagement study: what can your biz learn?", Birmingham Business Journal, 2, 1--4.Google Scholar
- Rheingold, H. (1993), The Virtual Community: Homestanding on the Electronic Frontier, Addison-Wesley. New York, NY. Google ScholarDigital Library
- Pace, Stefano, Luciano F., & Fabrizio C. (2007), Consumer Tribes. In Bernard Cova, Robert V. Kozinets, and Avi Shankar (Eds), Internationalization of a Craft Enterprise through a Virtual Tribe: 'Le Nuvole' and the Pipe Smoker Trib (pp 312--328). London, UK: Butterworth Heinemann.Google Scholar
- Kardaras, D. 2003. The potential of virtual communities in the insurance industry in the UK and Greece. International Journal of Information Management 23, 45--53. Google ScholarDigital Library
- Williams, R. L. and Cothrel, J., 2000. Four smart ways to run online communities. Sloan Management Review, 41(4), 81--91.Google Scholar
- Xema P. & Manisha P. S. (2017). Sentiment analysis of virtual brand communities for effective tribal marketing. Journal of Research in Interactive Marketing, 11(1).Google Scholar
- Hagel, J. III & Armstrong, A. G. (1997), Net Gain: Expanding Markets through Virtual Communities, Harvard Business School Press, Boston, MA. Google ScholarDigital Library
- Andersen, P. H. (2005), "Relationship marketing and brand involvement of professionals through web-enhanced brand communities: the case of Coloplast", Industrial Marketing Management, 34, 39--51.Google ScholarCross Ref
- Muniz Jr, A. M., & O'guinn, T. C. (2001). Brand community. Journal of consumer research, 27(4), 412--432.Google ScholarCross Ref
- Algesheimer, R., Dholakia, U. M., & Hermann, A. (2004). Interplay between brand and brand community: Evidence from European car clubs.Google Scholar
- Brodie, R. J., Ilic, A., Juric, B., & Hollebeek, L. (2013). Consumer engagement in a virtual brand community: An exploratory analysis. Journal of Business Research, 66, 105--114.Google ScholarCross Ref
- Kozinets, R. V. (1999). E-Tribalised Marketing?: The Strategic Implications of Virtual Communities of Consumption. European Management Journal, 17(3), 252--264.Google ScholarCross Ref
- Kozinets, R. V. (2001). Utopian enterprise: Articulating the meanings of Star Trek's culture of consumption. Journal of Consumer Research, 39(1), 61--72.Google Scholar
- Pang B. & Lee L. (2004). A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts. Proceedings of the Association for Computational Linguistics (ACL). 271--278. Google ScholarDigital Library
- Walaa M., Ahmed H., & Hoda K.. 2014. Sentiment analysis algorithms and applications: A survey. Ain Shams Engineering Journal, 5(4), 1093--1113.Google ScholarCross Ref
- Aurangzeb K., Baharum B., & Khairullah K. (2011). Sentiment classification from online customer reviews using lexical contextual sentence structure. In Software Engineering and Computer Systems, 317--331.Google Scholar
- AYLIEN, Text Analysis API. (n.d.). Retrieved May 11, 2017, from AYLIEN website http://aylien.comGoogle Scholar
- Monkeylearn, machine learning Analysis tools. (n.d.). Retrieved May 11, 2017, from Monkeylearn website, www.monkeylearn.comGoogle Scholar
- Stehman & Stephen V. (1997). Selecting and interpreting measures of thematic classification accuracy. Remote Sensing of Environment, 62 (1): 77--89.Google ScholarCross Ref
Index Terms
- Sentiment Analysis of Online Crowd Input towards Brand Provocation in Facebook, Twitter, and Instagram
Recommendations
Gratifications of using Facebook, Twitter, Instagram, or Snapchat to follow brands
Snapchat is used for passing time, sharing problems, and social knowledge.Instagram is used for showing affection, following fashion, and sociability.Twitter users had highest brand community identification and membership intention.Instagram users had ...
Social sentiment sensor: a visualization system for topic detection and topic sentiment analysis on microblog
As a new form of social media, microblogging provides platform sharing, wherein users can share their feelings and ideas on certain topics. Bursty topics from microblogs are the results of the emerging issues that instantly attract more followers and ...
Sentiment analysis and topic extraction of the twitter network of #prayforparis
ASIST '16: Proceedings of the 79th ASIS&T Annual Meeting: Creating Knowledge, Enhancing Lives through Information & TechnologySocial media includes a copious amount of sentiment-embodied sentences. Sentiment is described as "a personal belief or judgment that is not founded on proof or certainty," which may depict the emotional state of the user, such as happy, glad, terrified,...
Comments