AN OVERBROAD PATENT ON classifying mobile users based on who they call in a network - This application from Ericsson seeks to patent the idea of...Social network analysis applied to mobile phones...Keep PRISM free of patent licenses! 10 minutes of your time can help narrow US patent applications before they become patents. Follow @askpatents on twitter to help.

QUESTION - Have you seen anything that was published before 5/24/2010 that discusses:

  • Social network analysis to classify individuals in a community based on who they communicate with

If so, please submit evidence of prior art as an answer to this question. We welcome multiple answers from the same individual.

EXTRA CREDIT - A reference to anything that meets all of the criteria to the question above AND ALSO involves demographic information about users.

TITLE: Social network analysis on cell phone calling networks to segment users

Summary: [Translated from Legalese into English]

  • Publication Number: US20130138479 A1
  • Application Number: US 13/699,796
  • Assignee:
  • Prior Art Date: Seeking prior Art predating 5/24/2010
  • Open for Challenge at USPTO: Open through 11/26/2013

Claim 1 requires each and every step below:

A method for classifying a new mobile user in a communication network based on demographics associated with the new mobile user, the method comprising:

  1. Representing, for a sample set of mobile users, each mobile user in the sample set by a node and mobile usage between two nodes by an edge connecting the two nodes;

  2. Forming one or more communities of nodes;

  3. Identifying a plurality of demographic subunits by splitting each of the one or more communities;

  4. Determining one or more structural properties associated with each of the plurality of subunits;

  5. Mapping the one or more structural properties to demographics of the plurality of subunits; and

  6. Classifying the new mobile user based on the determined structural properties.

In English this means:

A method for classifying a new user in a communication network, comprising:

  1. Creating a graph structure with users as nodes and edges as communication between users

  2. Forming communities of nodes (using any clustering technique)

  3. Looking for correlation between demographic features of groups of nodes (e.g. rich, white, parent, etc…) and structural features of same groups of nodes (all communicate with one another, for example)

  4. Classifying a new user based on these structural features (i.e. who he talk to)

Good prior art would be evidence of a system that did each and every one of these steps prior to 5/24/2010

You're probably aware of ten pieces of art that meet this criteria already... separately, the applicant is claiming segmenting customers based on standard clustering algorithms applied to a social graph

"Determining and presenting demographics of mobile users in a communication network from the Applicant"

What is good prior art? Please see our FAQ.

Want to help? Please vote or comment on submissions below. We welcome you to post your own request for prior art on other questionable US Patent Applications.

1 Answer 1


Does this also suggest number of communications like amount of connections or it just considers 2 nodes connected using 1 connection and analysis of nodes.

I mean does it say that analysis would include how much time it took for the connection to stay live and also take into account how many time a connection was live etc.

  • No necessary limitation. In U.S., inventors may "act as their own lexicographer" in a patent application. That means that an inventor may give a common word or phrase a meaning that is very specific and different from the normal definition of said word or phrase. Thus a claim must be interpreted in light of the definitions provided in the specification of a patent. The specification for US20130138479 gives a number of examples but doesn't limit the analysis to the time connections remain live or frequency of connection. The only limitation is that method must contain each claim element above! Commented Nov 20, 2013 at 22:36

You must log in to answer this question.

Not the answer you're looking for? Browse other questions tagged .