Abstract
This paper attempts to use emotional analysis technology to analyze contemporary art criticism. We have collected about 5000 articles from eight journals over the past 60 years. For each article, SnowNLP and TextBlob are used for emotional analysis from three levels: the topic of the article, the abstract and all the sentences in the full text. The abstract is generated by TextRank technology. We calculated the probability density distribution of emotions at three levels for all articles in each year, and found that the proportion of negative emotions was much higher than that of positive ones. We compared the distribution of emotional probability density between different years and found no significant difference. We also conducted an emotional trend analysis of art reviews, and found that thematic emotions began to develop in a positive direction after 2000, while the emotions of abstracts and full-text sentences have basically been developing in a negative direction. The median of all years is lower than the average.
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