Social network integration and user content generation: Evidence from natural experiments

Ni Huang, Yili Hong, Gordon Burtch

Research output: Contribution to journalArticlepeer-review

30 Scopus citations

Abstract

This study examines how social network integration (i.e., integration of online platforms with other social media services, for example, with Facebook or Twitter) can affect the characteristics of user-generated content (volume and linguistic features) in the context of online reviews. Building on the social presence theory, we propose a number of hypotheses on how social network integration affects review volume and linguistic features of review text. We consider two natural experiments at leading online review platforms (Yelp.com and TripAdvisor.com), wherein each implemented a social network integration with Facebook. Constructing a unique panel dataset of online reviews for a matched set of restaurants across the two review sites, we estimate a difference-in-differences (DID) model to assess the impact of social network integration. We find that integration with Facebook increased the production of user-generated content and positive emotion in review text, while simultaneously decreasing cognitive language, negative emotion, and expressions of disagreement (negations) in review text. Our findings demonstrate that social network integration works as a double-edged sword. On the one hand, integration provides benefits in terms of increased review quantity. On the other hand, these benefits appear to come at the cost of reduced review quality, given past research which has found that positive, emotional reviews are perceived by users to be less helpful. We discuss the implications of these results as they relate to the creation of sustainable online social platforms for user content generation.

Original languageEnglish (US)
Pages (from-to)1035-1058
Number of pages24
JournalMIS Quarterly: Management Information Systems
Volume41
Issue number4
DOIs
StatePublished - Dec 2017

Bibliographical note

Funding Information:
The authors thank the senior editor, Sulin Ba, and the review team for a most constructive and developmental review process. The authors also thank Paul Pavlou, Susan Mudambi, and participants at the NET Institute Conference and International Conference on Information Systems for valuable feedback. The authors acknowledge financial support from the NET Institute (#15-04) and the Young Scholar’s Forum of Fox School of Business, Temple University.

Funding Information:
Information Systems, W. P. Carey School of Business at Arizona State University. She obtained her Ph.D. in Business Administration at the Fox School of Business, Temple University. Her research focuses on the behavioral and economic aspects of online and mobile platforms. Nina’s research has been published in premier journals, including MIS Quarterly, Journal of the Association for Information Systems, and Journal of Consumer Psychology. Her work has also been presented at premier conferences, such as the International Conference on Information Systems, Conference on Information Systems and Technology, Statistical Challenges in eCommerce Research, NET Institute Conference, and CODE@MIT. Her research has received funding from the NET Institute, the Fox School Young Scholar’s Forum, and Amazon Web Services (AWS). Nina is currently a external researcher and closely works with a number of companies, including Yamibuy, Meishi, and XuetangX.

Funding Information:
Yili (Kevin) Hong is an assistant professor and codirector of the Digital Society Initiative in the Department of Information Systems at the W. P. Carey School of Business of Arizona State University. He obtained his Ph.D. in Business Administration at the Fox School of Business, Temple University. Kevin’s research focuses on areas of the sharing economy, online platforms and user-generated content. His research has been published in premier journals such as Management Science, Information Systems Research, MIS Quarterly, Journal of the Association for Information Systems, and Journal of Consumer Psychology. He is the winner of the ACM SIGMIS Best Dissertation Award and runner-up of the INFORMS ISS Nunamaker-Chen Dissertation Award. His papers have won best paper awards at the International Conference on Information Systems, Hawaii International Conference on System Sciences, and the America’s Conference on Information Systems. Kevin’s research has received funding from a number of agencies, including the Robert Wood Johnson Foundation, NET Institute, and the Department of Education. He is an external research scientist for a number of high profile tech companies, including Freelancer, Fits.me, Yamibuy, and Meishi.

Funding Information:
sion Sciences at the University of Minnesota’s Carlson School of Management, and a Consulting Researcher with Microsoft Research, NYC. He holds a Ph.D. from Temple University’s Fox School of Business. His research has been published in various top journals, including MIS Quarterly, Information Systems Research, Management Science, and the Journal of Consumer Psychology. Gord’s work has been recognized with financial support from a number of granting agencies, including the Kauffman Foundation, 3M Foundation and NET Institute, and has been cited by a variety of major outlets in the popular press, including The New York Times, NPR, Time Magazine, Forbes, Vice, Wired, The Los Angeles Times, Pacific Standard, and PC Magazine. Gord was the recipient of the Information Systems Society’s Information Systems Research best paper award in 2014, the Distinguished Service Award from Management Science in 2016 and the Best Reviewer award from Information Systems Research in 2016. He served as cochair for the 2016 Workshop on Information Systems and Economics (WISE).

Keywords

  • Difference-in-differences
  • Natural experiment
  • Online reviews
  • Social network integration
  • Text analytics

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