Tagging Systems and
Their Effect on
Resource Popularity
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Tagging Systems on Flickr: Impact on Image Popularity, Slides of Data Communication Systems and Computer Networks
The use of tagging systems on flickr and their influence on image popularity. The research involves gathering data using visual studio .net and flickr api, converting it into bipartite networks, and analyzing through degree, betweenness, centrality, coefficiency, and other methods. Questions to be answered include the relationship between owners and images, owners and comments, and images and tags.
Typology: Slides
2012/2013
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Tagging Systems and
Their Effect on
Resource Popularity
Background & Related Work
- Taxonomy of Tagging Systems
- System design and attributes
- How the characteristics of a tagging system effects the content, the tags and the usage
- Users
- How their incentives and motivations affect the tagging system
- System design and attributes
Background & Related Work
Methodology
Converting Information
- Write script to separate data into multiple
bipartite networks in Pajek format
Converting Data
- Image/tags by a few different categories
- Separating into categories will be more accurate
- Possibly separate categories into popular, neutral and unpopular
- Image/Comments
- Owners/Images
- Owners/Comments
- This will give me many bipartite graphs to perform several different studies
Analyzing The Data
- New images will naturally have low number of views and will probably be removed from the study
- Flickr has a ‘Most Interesting’ section. I believe these are new images that are receiving a larger number of views than most
- These can be analyzed to see if they have tags or not and if they have an affect on the number of views an image is receiving.
Analyzing The Data
- Use Pajek, VS .net 2005
Analyzing The Data
- Find Coefficiency
- Image/Tags: see if images with a higher coefficiency are more popular
- Image/Comments: see if images that are commented on more are more popular
- And so on
Analyzing The Data
- Convert bipartite graphs into 1-mode
Questions To Be Answered
- Owner to Images
- Broken down by owner popularity
- See if users of high ranking has more popular images than users with low ranking
- Broken down by owner popularity
Questions To Be Answered
- Owners to comments
- See if the number of comments left by users on an owners profile is related to their popularity
- If so then check to see if the popularity of the users who left comments plays a role.
Questions To Be Answered
- Owners to Owners
- Does a user’s friend’s popularity affect their popularity? - Try to compare those with mostly popular friends to those with mostly unpopular (mostly non-active) friends
Questions To Be Answered
- Images to comments
- Similar to Owners to comments
- Do the comments left play a role in the image’s popularity? - Again, if it does then does the popularity of the users leaving the comments play a role?