Social Event Scheduling

TL;DR

This paper introduces the Social Event Scheduling (SES) problem, aiming to maximize event attendance by considering user preferences, conflicts, and competition, and proposes a greedy approximation algorithm validated on Meetup data.

Contribution

The paper formalizes the SES problem, proves its NP-hardness, and presents a novel greedy approximation algorithm for effective scheduling.

Findings

SES is strongly NP-hard even in restricted cases.

The proposed greedy algorithm performs well on real Meetup data.

Scheduling considering user preferences improves attendance.

Abstract

A major challenge for social event organizers (e.g., event planning and marketing companies, venues) is attracting the maximum number of participants, since it has great impact on the success of the event, and, consequently, the expected gains (e.g., revenue, artist/brand publicity). In this paper, we introduce the Social Event Scheduling (SES) problem, which schedules a set of social events considering user preferences and behavior, events' spatiotemporal conflicts, and competing vents, in order to maximize the overall number of attendees. We show that SES is strongly NP-hard, even in highly restricted instances. To cope with the hardness of the SES problem we design a greedy approximation algorithm. Finally, we evaluate our method experimentally using a dataset from the Meetup event-based social network.