The fear of loneliness has always driven humans towards joining different social (or political, cultural, ideological etc. The more specific types have been introduced in varying (increasing, to be exact) rates throughout the history.) groups of different scale and size. This kind of phobia, as any other type of phobia, changes from a minimal level to an extremely high one. Therefore, different people are afraid of being lonely on many different levels. One's fear level could be negligible, and the other's could be substantially dominant over the rest of his phobias. However, there could also be several other cases where the difference between the levels is essentially very small.
Generally, each individual's level has the potential of increasing (or decreasing) to another level if and only if it is influenced (or caused) to change by a new dominant set of changing factors. (A way to influence the neural progress)
This could all be represented by a ratio of two polynomials of degree, and order, n and m (where n is less than m). The coefficients of the n+m terms can be obtained by using a learning algorithm to estimate their accuracy. The bigger problem is the calculation of the exact values of n and m (in other words, finding the more dominant terms (i.e. characteristics) that influence the final value produced by the ratio on different crucial levels). This could be done by estimating these terms, and again, using a learning algorithm suitable for these terms and their own characteristics to correct and change the errors produced during the process.
It is necessary to apply some approximations while doing these calculations. However, respecting the extremely complex nature of each individual element should always be the first consideration.
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