An approach to identify influential building blocks and linkages in an information resource network

An information resource network (IRN) is a time-ordered and potentially interrelated set of information elements. Examples include papers within a research domain, blog postings dealing with a certain topic, and information records within a company. We present a structured analysis to identify influential building blocks and linkages in a general IRN and show that our approach can be used for large networks of information nodes. Our method compensates for biases that can emerge at the edges of such time-dependent networks. Importantly, our focus is on the information elements and not on the authors of such information. We illustrate this process using one example of a resource network — research papers in a given domain. Our method can be implemented in any domain that can be represented as time-ordered, interrelated components of information sets.

► Identify information resource network (IRN) important building blocks and linkages.
► Extremely useful in modeling directional, time-stamped and context-specific IRN.
► Focuses on information content and relevance, as opposed to author of information.
► Develops unbiased metrics to measure and highlight IRN elements and linkages.
► Can be used to identify and rank information sources too (journal, blog, network).