Abstract
Most studies on Black Friday have largely relied on survey or sales data from case studies of specific cities, which are lack of spatial-temporal granularity. The recent development of location-aware technologies has enabled what Goodchild described as “humans as sensors”, and as a result there has been a large volume of volunteered geographic information with explicitly spatial and temporal tags. Mining these rapidly growing and timely data in the context of space-time synthesis provides a new perspective for understanding the pulse of shopping behavior. In this chapter, we analyze Black Friday patterns and trends in the USA using a dataset retrieved from Twitter. A spatial-temporal analysis of tweeting patterns is conducted. This study tries to discern patterns of tweets on Black Friday in a comparative context.
| Original language | English (US) |
|---|---|
| Title of host publication | Urban and Regional Planning and Development |
| Subtitle of host publication | 20th Century Forms and 21st Century Transformations |
| Publisher | Springer International Publishing |
| Pages | 173-186 |
| Number of pages | 14 |
| ISBN (Electronic) | 9783030317768 |
| ISBN (Print) | 9783030317751 |
| DOIs | |
| State | Published - Jan 1 2020 |
| Externally published | Yes |
All Science Journal Classification (ASJC) codes
- General Environmental Science
- General Economics, Econometrics and Finance
- General Business, Management and Accounting
- General Social Sciences
Keywords
- Black friday
- Shopping behavior
- Spatial-temporal data
- Volunteered geographic information