1. A method of profile matching based on observed network behavior in a computer-implemented social network of a plurality of users, said method comprising: (a) observing network behaviors of at least some of said plurality of users of said social network, called observed users, wherein said network behaviors of each of said observed users comprise: (i) a customization of a visual graphic by the same of said observed users; (ii) a media preference of the same of said observed users; and (iii) a communication preference of the same of said observed users; (b) profiling at least some of said observed users based on said observed network behaviors of the same of said observed users, wherein said profiling is with respect to one or more domains, wherein said profiling comprises associating one or more scale factors for each of said observed network behaviors based on a relevance of the same of said observed network behaviors to said domain used in said profiling; (c) matching two or more of said profiled users with respect to the same of said domains, wherein said matching is based on said profiling; (d) rating said profile matching based on one or more user inputs of said matched profiled users, a participation data of said matched profiled users, or any combination thereof; and (e) updating said profiling by refining said scale factors based on said rating.
1. A method of profile matching based on observed network behavior in a computer-implemented social network of a plurality of users, said method comprising: (a) observing network behaviors of at least some of said plurality of users of said social network, called observed users, wherein said network behaviors of each of said observed users comprise: (i) a customization of a visual graphic by the same of said observed users; (ii) a media preference of the same of said observed users; and (iii) a communication preference of the same of said observed users; (b) profiling at least some of said observed users based on said observed network behaviors of the same of said observed users, wherein said profiling is with respect to one or more domains, wherein said profiling comprises associating one or more scale factors for each of said observed network behaviors based on a relevance of the same of said observed network behaviors to said domain used in said profiling; (c) matching two or more of said profiled users with respect to the same of said domains, wherein said matching is based on said profiling; (d) rating said profile matching based on one or more user inputs of said matched profiled users, a participation data of said matched profiled users, or any combination thereof; and (e) updating said profiling by refining said scale factors based on said rating. 4. The method as set forth in claim 1 , wherein said media preference is associated with a media content, a media type, a frequency of media playback, or any combination thereof.