A critical review on the research topic system of soil heavy metal pollution bioremediation based on dynamic co-words network measures

Abstract

From the perspective of dynamic co-words network, for the first time this paper provide a unique flavored critical review on the evolution of the research topic system (RTS) of soil heavy metal pollution bioremediation (SHMPB). We built the dynamic co-words network-related measures of the RTS of SHMPB. Several main innovative findings were obtained. (i) We got the basic characteristics of the co-words network. The co-words network for the RTS had a relative wide and flat structure, which implies the SHMPB's RTS has spread in a broad range. This is differently from the usual radial structure of RTSs in many other scopes. (ii) We revealed the hotspots and development trends of the RTS: the contact degree between different hot fields gradually has increased as the years go by. We found that researchers tended to use plants to carry out SHMPB. The hotspots have shifted from hyperaccumulators to the plants like poplar. (iii) From the degree distribution of the dynamic co-words network, we revealed the evolution of the RTS had the scale free characteristics. The growth and preferential attachment mechanism of keywords were the driving force of the evolving RTS. (iv) By the calculations of the average path length and average clustering coefficients, we found that the evolution of the RTS had the small-world effect. (v) Basing on the obtained results, we gave some implications such as the confirmation of high efficient information transmission, the identification of potential destructive effect, the recognition of important nodes and the creation of new information transmission path within the RTS. Beyond the RTS of SHMPB, we would like to stress the importance of the proposed method, demonstrating its universal applicable merits for RTSs in wide scopes.