Abstract

ABSTRACTWith as many as 4 million passenger journeys within the London Underground system every weekday, the advertisement spaces across the stations hold considerable potential. However, the planning of specific advertisements across time and space is difficult to optimize as little is known about passers-by. Therefore, in order to generate detailed and quantifiable spatio-temporal information which is particular to each station area, we have explored local social media data. This research demonstrates how local interests can be mined from geotagged Tweets by using Latent Dirichlet Allocation, an unsupervised topic modelling method. The relative popularity of each of the key topics is then explored spatially and temporally between the station areas. Overall, this research demonstrates the value of using Geographical Information System and text-mining techniques to generate valuable spatio-temporal information on popular interests from Twitter data.

Highlights

  • Conventional outdoor advertising, known as out-ofhome (OOH) advertising, focuses on marketing by means such as billboards and posters in public spaces (David, Yadav, and Donthu 2006)

  • The development of digital out-of-home (DOOH) advertisements with digital billboards makes outdoor advertising more flexible and enables the advertising schedules to respond to changes in their audiences across time (Lasinger and Bauer 2013)

  • More than 4 million passenger journeys are handled by London Underground system every day; advertising spaces in the stations are very profitable

Read more

Summary

Introduction

Conventional outdoor advertising, known as out-ofhome (OOH) advertising, focuses on marketing by means such as billboards and posters in public spaces (David, Yadav, and Donthu 2006). Considerable research and development has gone into devising more productive and targeted outdoor advertising strategies (Glover, Hartley, and Patti 1989; David, Yadav, and Donthu 2006; Cronin 2008). This is challenging in the case of OOH advertising as it is difficult to acquire detailed data on potential audiences in public places, especially given that they may change routinely throughout the week. The London Underground system is dedicated to serve London’s population of 8.5 million persons, in addition to those who visit the city for work or leisure purposes.

Objectives
Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call