Each era and each person has their own unique aesthetics and preferences, so different people may have different answers to the question of who is the best poet.
Big data can analyze and mine large amounts of data and provide some useful information and trends, but it cannot completely accurately reflect a person's talents and achievements. Furthermore, even with the help of big data, we are not entirely sure which poets are the best. Because the excellence of poetry depends not only on the statistical results of data.
It is also related to personal aesthetics, cultural background, emotional experience and other factors. Therefore, we cannot determine the level of Li Bai's poetry based solely on the ranking of big data. When appreciating poetry, we should respect everyone's creativity and uniqueness, and not pursue rankings and data too much, but focus on the connotation and beauty of the poetry itself.
If we only talk about the reputation of the poet himself, Li Bai must be recognized as the number one poet in the Tang Dynasty, or in the entire feudal history of China. Li Bai's life is extremely legendary, and his poems are full of romanticism without losing the ethereal and fairy spirit, so he is known as the Immortal of Poetry.
Li Bai has 980 existing poems, each of which can be said to be astonishing to read. However, there are two representative poems among Li Bai’s many poems, which can definitely be regarded as the pinnacle of all types of his poetry. .
The advantages of big data analysis in poetry evaluation:
1. Quantitative analysis: Big data can quantitatively analyze various characteristics of poetry, such as word usage, sentence structure, imagery, emotion, etc. , so as to objectively and accurately evaluate the style, characteristics, quality and other aspects of poetry.
2. Discover patterns: Big data can analyze a large number of poems to discover patterns and trends, such as changes in poetry style, development of genres, etc., so as to better understand the evolution and development of poetry. .
3. Personalized recommendation: By analyzing users’ reading habits and preferences, big data can provide users with personalized poetry recommendation services, helping users better discover and appreciate poems that suit them. .
4. Interdisciplinary integration: Big data analysis can be combined with literature, psychology, philosophy and other disciplines to provide a broader vision and deeper understanding for poetry evaluation.