Approximating the Community Structure of the Long Tail

In many social media applications, a small fraction of the members are highly linked while most are sparsely connected to the network. Such a skewed distribution is sometimes referred to as the "long tail". Popular applications like meme trackers and content aggregators mine for information from only the popular blogs located at the head of this curve. On the other hand, the long tail contains large volumes of interesting information and niches. The question we address in this work is how best to approximate the community membership of entities in the long tail using only a small percentage of the entire graph structure. Our technique utilizes basic linear algebra manipulations and spectral methods. It has the advantage of quickly and efficiently finding a reasonable approximation of the community structure of the overall network. Such a method has significant applications in blog analysis engines as well as social media monitoring tools in general.
Date: March 31, 2008
Book Title: Proceedings of the Second International Conference on Weblogs and Social Media (ICWSM 2008)
Type: InProceedings
Publisher: AAAI Press
Organization: AAAI
Note: Poster Paper; To Appear
Downloads: 1710

Has 2 soft copies

size 4663957 bytes

size 595968 bytes


  author = "Akshay Java and Anupam Joshi and Tim Finin",
  title = "{Approximating the Community Structure of the Long Tail}",
  month = "March",
  year = "2008",
  organization = "AAAI",
  note = "Poster Paper; To Appear",
  booktitle = "Proceedings of the Second International Conference on Weblogs and Social Media (ICWSM 2008)",
  publisher = "AAAI Press",