Abstract
Social media provide a fast-moving ecosystem for the rapid dissemination of digital maps. Some maps become viral, reaching massive audiences across diverse networks. A new challenge for cartographers is to characterize the design and dissemination of viral maps in social media. Here, we present a prototype visualization tool called MapReverse which allows users to explore collections of map images that are similar to a given viral map. Similar maps are identified using a combination of reverse image search and machine learning image analysis. In some cases, we can identify original sources for maps; more commonly we can identify many modifications of the original viral maps. This system provides a glimpse into the evolution of cartographic design as found in viral social media.
Original language | English (US) |
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Pages (from-to) | 91-97 |
Number of pages | 7 |
Journal | GI_Forum |
Volume | 10 |
Issue number | 1 |
DOIs | |
State | Published - 2022 |
All Science Journal Classification (ASJC) codes
- Geography, Planning and Development
- Education
- Computer Science Applications
- Computers in Earth Sciences