Predicting the near-weekend ticket sales using web-based external factors and box-office data

Seonghoon Moon, Suman Bae, Songkuk Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Posting online reviews and rating their satisfaction on purchased products has become an increasingly popular way to share the information for anonymous candidates who has interest in purchasing the product. In addition, people leave their interests and near-future purchasing plan on the web such as search history and search query volume. From this phenomenon, the prediction of sales performance is possible in many products by mining the data sets which are left on the web by consumers' online activities. In this paper, we focused on the movie ticket sales which word-of-mouth effect is prominent, and our goal is to forecast the sales performance of the near-weekend using box-office data and external factors such as online reviews, star ratings and search volume. For this work, we gather 1.7 million online reviews and movie ratings, and we also gather the daily search volume of movies' title for past three years. Using machine learning techniques and linear modeling, we develop a model for high-accuracy predicting of ticket sales on near-future. We also analyze a relationship between ticket sales performance on weekends and box-office data, online reviews, star ratings, and search volume. Through this work, we support to decide the ideal number of screens for a given weekend, thus it contributes to a substantial increase in the rate of profit on movie markets.

Original languageEnglish
Title of host publicationProceedings - 2014 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 2014
EditorsYuefeng Li, Lipika Dey, Andrzej Skowron, Adam Krasuski
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3-31
Number of pages29
ISBN (Electronic)9781479941438
DOIs
Publication statusPublished - 2014 Oct 16
Event2014 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 2014 - Warsaw, Poland
Duration: 2014 Aug 112014 Aug 14

Publication series

NameProceedings - 2014 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 2014
Volume2

Other

Other2014 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 2014
CountryPoland
CityWarsaw
Period14/8/1114/8/14

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Software

Fingerprint Dive into the research topics of 'Predicting the near-weekend ticket sales using web-based external factors and box-office data'. Together they form a unique fingerprint.

  • Cite this

    Moon, S., Bae, S., & Kim, S. (2014). Predicting the near-weekend ticket sales using web-based external factors and box-office data. In Y. Li, L. Dey, A. Skowron, & A. Krasuski (Eds.), Proceedings - 2014 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 2014 (pp. 3-31). (Proceedings - 2014 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 2014; Vol. 2). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WI-IAT.2014.113