Social network analysis is associated with network theory and it has actually developed as a main technique in modern sociology. Biology, geography and also information science among many other kinds of scientific groups find the study of social networking to be even more important than before as time goes on. The methodology of social network has no doubt been presented in a bad light in the past due to the complex nature of the entire development of the analysis. Social network analysis with its theoretical statement, analysis procedure, methods, software, and researches, it has now moved from metaphor to paradigm. Network analysis is believed to have discrete methods in order to gather data and to get statistical analysis which makes it even harder to gain credibility, acknowledgement and support throughout the scientific world.
Analysts do have some trouble coming to agreements in certain aspect of human relationships form one to another. Analysts study two principles in this technique which include complete networks as well as specific population information within personal communities. The distinction between complete and egocentric analysis greatly depends on gathering data in regard to specific topics. The network analysis is concentrated mainly on groups such as schools and also analysts are required to collect information about participants in each particular analysis. Used with the combination of random sampling, egocentric analysis is very easy when compared with complete analysis.
Direct observation, questionnaires and even expirements are used to gather specific social network information. Actions, kinship, cognitions, distance, and co-occurrence are all representations fo the information gathered for studies. The main levels that are used in this analysis are subgroup levels, relation level and social network levels. The field of social network analysis is being conventionally knocked for the methodological methods followed with very little theoretical knowledge.
The problem with social network analysis in the past was due to the inability to test the thesis statistically, because the data violates assumptions and auto correlations. Thanks to the use of permutation testing, new breakthourghs are being found and therfor the studies are becoming more accepted. The present problem is due to the lack of enough computing resources to bound social networks as the datasets are very large, which make the process of data very difficult.