Open Collections

On social event organization

University of British Columbia

Online platforms, such as Meetup and Plancast, have recently become popular for planning gatherings and event organization. However, there is a surprising lack of studies on how to effectively and efficiently organize social events for a large group of people through those platforms. This thesis provides the first systematic study on key computational problem involved in organization of social events. We understand the Social Event Organization problem as assigning a set of events for a group of users to attend, where the users are socially connected with each other and have innate levels of interest in those events. We then introduce a set of formal definition of a restricted version of the problem and show that it is NP-hard and is hard to approximate. We propose efficient heuristic algorithms that improve upon simple greedy algorithms by incorporating the notion of phantom events and by using look-ahead estimation. Using synthetic datasets and three real datasets including those from the platforms Meetup and Plancast, we experimentally demonstrate that our greedy heuristics are scalable and furthermore outperform the baseline algorithms significantly in terms of achieving superior social welfare.

Text

2016-04-25

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/57862

Computer Science

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/