Time Reversed Delay Differential Equation Based Modeling Of Journal Influence In An Emerging Area

Abstract

A recent independent study resulted in a ranking system which ranked Astronomy and Computing (ASCOM) much higher than most of the older journals highlighting its niche prominence. We investigate the notable ascendancy in reputation of ASCOM by proposing a novel differential equation based modeling. The modeling is a consequence of knowledge discovery from big data-centric methods, namely L1-SVD. The inadequacy of the ranking method in explaining the reason behind the growth in reputation of ASCOM is reasonable to understand given that the study is post-facto. Thus, we propose a growth model by accounting for the behavior of parameters that contributes to the growth of a field. It is worthwhile to spend some time in analyzing the cause and control variables behind rapid rise in reputation of a journal in a niche area. We intend to identify and probe the parameters responsible for its growing influence. Delay differential equations are used to model the change of influence on a journals status by exploiting the effects of historical data. The manuscripts justifies the use of implicit control variables and models those accordingly that demonstrates certain behavior in the journal influence.