Link Analysis
Link analysis is a type of network analysis that involves studying the links or connections between entities, such as web pages, people, or organizations. In the World Wide Web context, link analysis is often used to study the structure of hyperlinks between web pages, identify patterns and relationships that can be used to understand the web's organization, and improve search engine algorithms.
Link analysis techniques can also be used in other domains, such as social network analysis, where they can help to identify key players and relationships within a network, and in fraud detection, where they can be used to detect patterns of fraudulent behavior.
Some standard techniques used in link analysis include:
- PageRank: This algorithm, developed by Google co-founder Larry Page, uses the structure of hyperlinks between web pages to assign a score to each page based on its importance.
- HITS (Hypertext Induced Topic Selection): This algorithm, developed by Jon Kleinberg, uses the links between web pages to identify authoritative sources and hubs of information.
- Centrality measures: These measures, such as degree centrality and betweenness centrality, can be used to identify nodes within a network that are particularly important or influential.
- Community detection: This technique involves identifying group nodes within a network that are more densely connected than nodes outside the group.
Overall, link analysis is a powerful tool for understanding the relationships between entities within a network, and it has numerous applications in various domains.