<span>Fuzzy Graphs are used for analyzing and modeling levels of information<br /><span>in real-time systems (simple or complex networks). A community<br /><span>(network) is formed when human eProfiles (nodes) have links (edges)<br /><span>and interactions with each other. Considering multiple medium of<br /><span>communications like email, chatting and short message service (SMS)<br /><span>in the network, it will make the graph more complex (dense graph or<br /><span>forest). To address this issue in this paper analyzes those human<br /><span>communities with the help of fuzzy graphs and highlights the status of<br /><span>individuals in a human community. Max-Min Composition (fuzzy<br /><span>relation) was applied along with statistical analysis on fuzzy graphs of<br /><span>human community. Interaction Index (II) is used to estimate the intensity<br /><span>of communication and Role Index (RI) determine the participation status<br /><span>of individual in a human community. All this analysis will be used in<br /><span>our research and development of Community Algorithm, which will be<br /><span>used as a tool that will help in identifying, analyzing, manipulating,<br /><span>monitoring, and transforming human communities based on human<br /><span>eProfiles.</span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span><br /><br class="Apple-interchange-newline" /></span>