Service Area

Community Detection in Social Networks

Area: Marketing

Identifying people with similar needs, interests, habits, and characteristics for users to participate in a community or for a company to identify targets for marketing.

With the development of an evolutionary algorithm, we have designed an effective technique to help users identify a particular community that they can join to either share what they have in common with the others or to learn from and know more about the others that are within the same community. Our technique can also be used to identify communities that share common interests, habits, political views, etc. for target marketing.

Unlike other techniques for discovering communities in social networks, the evolutionary algorithm that we have developed takes into account, not just network topologies, but it also considers the attributes that each member in a social network shares. As a result, users in the same community are not just connected more frequently with each other, but they also share similar characteristics.

- Special Features and Advantages

  • Discovers more than one community to which each person can belong.
  • Discovers community of people that share common attributes.
  • The evolutionary algorithm can be implemented on parallel machines to allow community detection of a very large network to be discovered in a very short time.

- Applications

  • Identification of community structure of complex networks.
  • Social network analysis.
  • Target marketing, advertising, and promotion in social networking service sites.
  • Automatic recommendation to users to join communities in social networks.