Yang, Mochen2018-08-142018-08-142018-05https://hdl.handle.net/11299/199062University of Minnesota Ph.D. dissertation. May 2018. Major: Business Administration. Advisors: Yuqing Ren, Gediminas Adomavicius. 1 computer file (PDF); ix, 196 pages.Social media platforms such as Facebook empower individual users to interact with companies and with each other on company-managed business pages. Users can generate content by posting directly to the business pages, and other users can engage with the content through multiple engagement features. Although such user-generated content (UGC in short) and associated engagement behaviors bear important consequences to the companies, they are not well understood. The three essays of my dissertation fill in this gap, by analyzing data collected from Facebook business pages with multiple empirical methods. The first essay examines the valence and content characteristics of user-generated posts on the Facebook business pages of multiple large companies across key consumer-oriented industries. It demonstrates that user posts on Facebook business pages represent a new form of UGC that is distinct from online product reviews generated by consumers, in terms of valence distribution and content types. Further, it highlights the important valence and content factors that influence two canonical types of engagement activities, i.e., liking and commenting. The second essay discusses how user engagement behaviors are shaped by engagement features on Facebook, and in particular, how the introduction of a new engagement feature affects the usage of existing features as well as overall engagement activities. It aims to uncover new insights regarding the interplay of multiple engagement features. Analyses show that, despite distinct functionalities, the usage of different features is not independent, and user posts that have received engagement are likely to obtain even more engagement of various types. The third essay addresses a methodological challenge of studying UGC on social media or other online contexts, where researchers frequently seek to combine data mining with econometric modeling, but ignore the issue of measurement error and misclassification. Findings of my dissertation advance understanding of UGC and engagement behavior on social media brand pages, and have practical implications for social media platforms as well as businesses that have presence on these platforms.enThesis or Dissertation