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Another important application is sentiment analysis, which enables the
identification of emotional tones within literary texts. This approach is particularly
useful for exploring historical and cultural contexts. In his study “Mapping
Melancholy: Sentiment Analysis of Emotional Trends in Victorian Literature,” Prakash
identified patterns of emotions such as melancholy, joy, and anger, offering valuable
insights into the socio-cultural environment of the 19th century. By analyzing a large
body of texts from that period, AI can trace shifts in emotional expression in relation
to historical developments, such as the Industrial Revolution, thus illustrating how
societal transformations influenced literary output.
c. Comparative Literature Studies
AI also plays a crucial role in comparative literature by enabling the analysis of
texts across diverse languages and cultural backgrounds. As Beguš notes, the
development of AI systems in multiple languages provides a unique opportunity to
compare different national literatures and cultural traditions. AI-driven analysis can
examine both Western and Eastern literary works, identifying similarities and
differences in narrative techniques, themes, and character archetypes. Such
comparisons contribute to a deeper understanding of global literary traditions and
cultural exchanges.
d. Evolution of Literary Styles
Machine learning algorithms can also be utilized to trace the evolution of
literary styles over time. For example, an AI-based study might analyze American
literature from the 18th century to the modern era. By examining a large collection
of texts, AI can detect stylistic shifts, such as the movement from formal, structured
prose to more diverse and informal contemporary styles. This type of analysis
provides insights into the influence of historical, cultural, and technological
developments on literary expression.
e. Discovery of Hidden Patterns
AI tools are also effective in uncovering overlooked patterns and connections
within literary history. Researchers have applied AI techniques to analyze lesser-
known works by minor authors and poets, revealing relationships and influences that
were previously unnoticed. This process can lead to the rediscovery of significant
literary contributions and a more comprehensive understanding of literary
development.
Educational Impact
AI-powered technologies are also reshaping literary education by offering
interactive and engaging methods for exploring texts. Digital platforms that
incorporate AI-based analysis allow students to visualize complex literary structures,
monitor character development, and examine thematic elements in a more dynamic
way. This experiential approach encourages critical thinking and enhances students’
overall comprehension and appreciation of literature.

CONCLUSION
Artificial intelligence is transforming literary analysis by making advanced
analytical tools accessible to a wider audience and promoting interdisciplinary
collaboration. By utilizing AI technologies, researchers, educators, and readers can
engage with literary works in innovative ways, uncovering patterns and insights that
deepen textual understanding. This shift not only broadens access and inclusivity but 442
also drives the ongoing evolution of literary studies in the digital era.

III SHO‘BA:

Jahon adabiyoti tadqiqotlarida sun’iy intellekt yordamida badiiy matnlarni
tahlil qilish va interpretatsiya masalalari
https://www.asr-conference.com/