This research parsed entries of eight contemporary art journals from 1960 to 2015 by Natural Language Processing (NLP) and got 7000 words. These words were then analyzed by three methods: 1) word frequency, 2) word frequency trend analysis based on linear regression, and 3) word frequency variation model analysis based on curve clustering. The data were classified into a five-category set and a ten-category set, along with a ten-word-frequency-variation-model. Based on the above data study, this paper analyzed the resulted trends from political, economical, technological and art perspectives. The conclusion is that hot topics in American contemporary art vary with contemporary social backgrounds.
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