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Parsing Related Tags Networks from Flickr® to Explore Crowd-Sourced Keyword Associations

  • Shalin Hai-JewEmail author
Chapter
Part of the Multimedia Systems and Applications book series (MMSA)

Abstract

With the broad popularization of content-sharing social media platforms, researchers have developed methods to extract information from social related metadata. One approach is to extract related tags networks from freeform “folk” tags (keywords) used to describe imagery from Flickr®. These tag networks, graphed at 1, 1.5, and 2 degrees, show co-occurrence of related tags (above a certain threshold) to a target seeding tag. This work describes how these networks may be acquired and different ways that the extracted data may be used analytically in a digital humanities context.

Keywords

Application Programming Interface Giant Component Graph Density Social Media Platform Unique Edge 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Kansas State UniversityManhattanUSA

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