This paper focuses on exploring the information flow transfer effect in English and American literature using an improved semantic Web mining algorithm. On the basis of the traditional semantic Web mining algorithm, the three factors of depth, branching degree and occurrence probability in the ontology hierarchical tree are added to determine the semantic weights of the text and the semantic distance information. Then, the “author-text-reader” interpretation mechanism is proposed. A questionnaire was used to discuss the influence of the interpretation mechanism of this paper on readers’ acceptance of English and American literature. Among the more popular literary works on the online platform, the frequency of “novels” and “foreign literature” is higher, 30 and 27 respectively. The main information flow delivery platform on Weibo, accounting for 69.2% of the total, and the main delivery area is concentrated in the coastal area. British and American literature has had a great influence on Chinese literature. Using the “author-text-reader” interpretation mechanism, most of the interviewees can deeply understand literary works such as The Catcher in the Rye and The Great Gatsby.