Author ORCID Identifier

Tsai -

Document Type

Conference Proceeding

Publication Date


Publication Title

HT : Proceedings of the 27th ACM Conference on Hypertext and Social Media


July 2016

First Page


Last Page



On-line reviewing systems have become prevalent in our society. User-provided reviews of local businesses have provided rich information in terms of users' preferences regarding businesses and their interactions in reviewing systems; however, little is known about how the reviewing behaviors of users can benefit businesses in terms of suggesting potential collaboration opportunities. In the current study, we aim to build a recommendation system for businesses to provide suggestions for business collaboration. Based on historical data from Yelp that shows two businesses being reviewed by the same users within a same season, we were able to identify businesses that might attract the same customers in the future, and hence provide them with a collaboration suggestion. Our results suggest that the evidence - two businesses sharing reviews from same users - can provide recommendations for businesses to pursue future collaborative marketing opportunities.


© {Author | ACM} {2016}. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in {HT : Proceedings of the 27th ACM Conference on Hypertext and Social Media},