Brands all a Twitter: The influences of Twitter on brands and consumers

Open Access
Zhang, Mimi
Graduate Program:
Information Sciences and Technology
Doctor of Philosophy
Document Type:
Date of Defense:
September 02, 2010
Committee Members:
  • Bernard James Jansen, Dissertation Advisor
  • Bernard James Jansen, Committee Chair
  • Lynette Marie Yarger, Committee Member
  • Shawn Clark, Committee Member
  • James Landis Rosenberger, Committee Member
  • Abdur Chowdhury, Committee Member
  • online word-of-mouth
  • tweet analysis
  • social media
  • Twitter
Local, national, and global commercial businesses continue to be increasingly interested in leveraging Twitter to present the brand, manage word-of-mouth communication, and interact with consumers. However, there is a general lack of solid and comprehensive understanding of the platform. This dissertation attempts to fill that gap by providing an in-depth analysis of word-of-mouth communications among consumers and businesses on Twitter and by uncovering Twitter community dynamics from a business perspective. I examined three aspects important to current and prospective business Twitter users, namely benefit (i.e., what can a business get from Twitter?), role (i.e., how active should a business be on Twitter?), and audience (i.e., who connects to a business on Twitter?). To address my research questions, I collected approximately 2 million tweets pertaining to nine brands from May, 2008, to May, 2009. I performed bootstrap-based nonparametric analysis of variance to address the benefit question and found that following a brand or being followed by a brand has statistically significant main effect on the number of word-of-mouth messages consumers send out as well as the number of word-of-mouth conversations that consumers participate in with other consumers and the brand. I conducted path analysis to explore questions about a business’ role and discovered that as an active participant in the word-of-mouth dialogue, a business can increase the engagement level of consumers in word-of-mouth communication. I carried out TwoStep cluster analysis to analyze audience makeup and identified five types of consumers in a brand’s immediate social network. This dissertation advances the understanding of the potential business value of Twitter deployment and brand management. This work provides insights about the analytics of social networking on micro-communication platforms such as Twitter. Considering that online word-of-mouth marketing is one of the most effective brand enhancing and selling tools, this work offers guidance to brands on the ways to approach customers, communicate with them, and persuade them to talk about the brands.