The spread of media content through the blogosphere
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TU Berlin Deutsche Telekom Lab. Flash Floods and Ripples:. Meeyoung Cha. Juan A. Navarro Max Planck Institute for Software Systems (MPI-SWS). Hamed Haddadi. The Spread of Media Content through the Blogosphere . ICWSM Data Challenge 2009. Motivation. How does content spread in blogs?

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The spread of media content through the blogosphere l.jpg

TU Berlin Deutsche Telekom Lab

Flash Floods and Ripples:

Meeyoung Cha

Juan A. Navarro

Max Planck Institute for Software Systems (MPI-SWS)

Hamed Haddadi

The Spread of Media Content through the Blogosphere

ICWSM Data Challenge 2009


Motivation l.jpg
Motivation

How does content spread in blogs?

What kinds of content are shared?

  • Blogs play a significant role in today’s Internet culture

  • Blogs are used for information propagation purposes

    • Discuss political issues

    • Review new products and online contents

    • Form communities and special interest groups

  • Increasingly, media content is shared through blogs


Our goal l.jpg
Our goal

  • Characterizehow the structure of the blogosphere influences the patterns of content spreading

  • 1. Understand the structure of the blogosphere

    • Is the structure ideal for content dissemination?

  • 2. Understand the spreading patterns of content

    • What types of content spread?

    • How quickly does content spread?


Part1 measurement methodology l.jpg

Part2. Analysis of network properties

Part3. Analysis of spreading patterns

Part1. Measurementmethodology


Spinn3r dataset l.jpg
Spinn3r dataset

  • Extracted post URL, site, host, language, timestamps, etc.

    • Step1: Focus on top 15 blog domains

    • Step2: Scrape content to find embedded HTML links

    • Code available at http://www.mpi-sws.org/~jnavarro/tools/

  • Limitations

    • Comments and blogrolls missing

    • Some blogs only post summaries

    • Only used dataset with numbered ‘tiers’



Step2 extracting html links l.jpg
Step2: Extracting HTML links

Links tomedia content

Links toother blogs


Part1 measurement methodology8 l.jpg

Part2. Analysis of network properties

Part3. Analysis of spreading patterns

Part1. Measurementmethodology


Network of blogs l.jpg
Network of blogs

Directed network of 85,013 nodes and 129,079 edges

A

B


Network structure l.jpg
Network structure

[ 73% of blogs in the largest connected component ]

Average node degree 1.5

Power-law degree distribution

6% of links are reciprocal

35% of links cross blog domains

7% of links cross language boundaries


Network structure 2 l.jpg
Network structure – 2

Network structure is more sparse than social networks

Density = Ratio of observed links, out of all possible links


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Insights for information propagation

  • Sparse structure & power-law degree distribution

    • Clear preference for bloggers to particular topics or sources

    • Trend setters (high in-degree) and recommenders (high out-degree)

  • Potential factors that can limit spreading

    • Blog domains had no visible effect on linking

    • Language barriers inhibit the flow of information


Part1 measurement methodology13 l.jpg

Part2. Analysis of network properties

Part3. Analysis of spreading patterns

Part1. Measurementmethodology


Spreading of media content l.jpg
Spreading of media content

media

  • What types of content are shared?

  • How quickly does information spread?


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Types of content shared

Popular sharing of user-generated content


Popularity of youtube videos l.jpg
Popularity of YouTube videos

  • Video popularity follows a power-law distribution:

  • Very large diffusion processes exist

  • Preferential attachment may drive linking


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Popular video categories

Musicmost popular

Still spread!

Keen onpolitics

We downloaded metadata of top 10,000 videos


Time lag in the spread of videos l.jpg
Time lag in the spread of videos

Flash floods

Ripples


Example spreading pattern l.jpg
Example spreading pattern

Blogs linking the same video are connected

= Diffusion through the blogosphere

Other

McCain’s political campaignlinked by 79 blogs


Insights from spreading patterns l.jpg
Insights from spreading patterns

  • Videos in different genres spread with very different patterns

    • Flash floods: found quickly and spread rapidly

    • Ripples: took longer to spread, re-discovered years after upload

  • Diffusion through links in the blogosphere

    • 24% of videos had any spreading in the blog graph

    • Other spreading factors: featuring and search


Part1 measurement methodology21 l.jpg

Part2. Analysis of network properties

Part3. Analysis of spreading patterns

Part1. Measurementmethodology


Conclusion l.jpg
Conclusion

  • Identified spreading patterns and factors that limit spreading

  • Blogs serve as a medium to filter and spread media content

  • Potential implication: Recommendation systems can take into account and exploit different spreading patterns

  • Future work: spreading patterns of other types of content


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