Intra-firm information flow: A content-structure perspective

Yakir Berchenko, Or Daliot, Nir N. Brueller

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


This paper endeavors to bring together two largely disparate areas of research. On one hand, text mining methods treat each document as an independent instance despite the fact that in many text domains, documents are linked and their topics are correlated. For example, web pages of related topics are often connected by hyperlinks and scientific papers from related fields are typically linked by citations. On the other hand, Social Network Analysis (SNA) typically treats edges between nodes according to "flat" attributes in binary form alone. This paper proposes a simple approach that addresses both these issues in data mining scenarios involving corpora of linked documents. According to this approach, after assigning weights to the edges between documents, based on the content of the documents associated with each edge, we apply standard SNA and network theory tools to the network. The method is tested on the Enron email corpus and successfully discovers the central people in the organization and the relevant communications between them. Furthermore, Our findings suggest that due to the non-conservative nature of information, conservative centrality measures (such as PageRank) are less adequate here than non-conservative centrality measures (such as eigenvector centrality).

Original languageEnglish
Title of host publicationAdvances in Intelligent Data Analysis X - 10th International Symposium, IDA 2011, Proceedings
Number of pages9
StatePublished - 2011
Externally publishedYes
Event10th International Symposium on Intelligent Data Analysis, IDA 2011 - Porto, Portugal
Duration: 29 Oct 201131 Oct 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7014 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference10th International Symposium on Intelligent Data Analysis, IDA 2011


  • Natural language processing
  • information flow
  • social network analysis

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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