Description:DESCRIPTION
Technical Field of the Invention

The present invention relates to the field of humanities computing, specifically to systems and methods for qualitative analysis of literature. More particularly, it pertains to a computerized system and method for analyzing representations of postcolonial trauma and gendered violence within literary narratives to generate structured insights, thematic mappings, and sociocultural interpretations.

Background of the Invention

The analysis of postcolonial trauma and gendered violence within literary narratives has been a critical focus in the fields of literary studies, cultural studies, and postcolonial theory. Traditionally, scholars engage in manual reading, interpretive critique, and thematic categorization to explore how literature reflects the experiences of colonization, displacement, racial subjugation, sexual exploitation, and gendered oppression. However, these manual methods are often time-consuming, subjective, and limited by individual cognitive capacities, leading to inconsistent interpretations and lack of systematic comparative analysis across multiple texts.

While general digital humanities tools exist for text analysis, such as word frequency counters, concordance generators, and topic modeling software, these tools do not integrate the theoretical frameworks of trauma studies and gender studies required for nuanced interpretation. Specifically, they lack specialized lexicons and taxonomies that identify literary representations of trauma, such as silence, dissociation, or testimonial rupture, and gendered violence, such as sexual violence, domestic abuse, or intersectional oppression in postcolonial contexts.

Further, current tools do not contextualize identified themes within the broader narrative structures, such as shifts in focalization, narrative voice, temporal distortions, or metafictional interventions that are critical in representing trauma and gendered violence. This gap limits the potential of digital tools to advance critical scholarship in literature, especially in postcolonial studies where cultural, historical, and political factors interrelate deeply with literary representations.

Accordingly, there exists a need for a computerized system and method that integrates trauma theory lexicons, gendered violence taxonomies, and narrative structure models into a unified analytical platform. Such a system will enable structured, reproducible, and scalable analyses of literary texts, facilitate rigorous, interdisciplinary research and enhance the pedagogical and scholarly understanding of postcolonial trauma and gendered violence in literature.

Objects of the Invention

The primary objective of the invention is to provide a computerized system that enables comprehensive analysis of postcolonial trauma and gendered violence representations within literary narratives.

Yet another objective of the invention is to integrate trauma theory lexicons and gendered violence taxonomies into automated text analysis tools for accurate thematic identification and categorization.

Yet another objective of the invention is to analyse narrative structures such as focalization, temporal distortion, and metafictional techniques that contextualize trauma and violence representations in literature.

Yet another objective of the invention is to generate structured outputs, including thematic reports and visualizations, to aid scholars in interpreting complex interrelations of trauma, gender, and postcolonial experiences within texts.

Yet another objective of the invention is to facilitate interdisciplinary and comparative research by providing a scalable, reproducible platform for analysing multiple texts across regions, authors, and time periods.
Brief Summary of the Invention

The present invention relates to a computer-implemented system and method for analyzing postcolonial trauma and gendered violence within literary narratives, addressing the limitations of manual interpretive analysis in literary studies. The system comprises an input module to receive digitized literary texts along with metadata such as author, publication year, and region. The preprocessing module applies natural language processing (NLP) functions including tokenization, lemmatization, stop-word removal, part-of-speech tagging, and named entity recognition to extract linguistic features essential for analysis.

The invention’s core is an analysis engine integrating a trauma theory submodule and a gendered violence submodule. The trauma theory submodule identifies representations such as dissociation, silence, fragmentation, and testimonial rupture, while the gendered violence submodule classifies violence into categories like sexual violence, domestic abuse, honor-based violence, and intersectional oppression. Additionally, a narrative structure analyzer examines narrative voice, focalization shifts, temporal distortions, and metafictional interventions to contextualize trauma and violence representations within the literary work.

The database module stores processed texts, annotations, and thematic classifications for comparative analysis, while the output module generates structured reports and visualizations such as heat maps, network graphs, and timelines. The invention thus facilitates systematic, scalable, and interdisciplinary literary analysis, enhancing scholarly research, teaching, and digital humanities archiving in postcolonial and gender studies.

Brief Summary of the Drawings

The invention will be more clearly understood from the following brief description of the accompanying drawings, which illustrate exemplary embodiments of the present invention and are intended to support the detailed disclosure by highlighting the structural and functional aspects of the system.

Fig. 1 is a schematic block diagram illustrating the architecture of the system, in accordance with the exemplary embodiment of the invention;

Fig. 2 illustrates the data flow from text input to thematic analysis output, in accordance with the exemplary embodiment of the invention;

Fig. 3 depicts a sample visualization output showing trauma and gendered violence mappings across multiple texts, in accordance with the exemplary embodiment of the invention;

Fig. 4 shows the interface design for uploading texts and accessing analysis results, in accordance with the exemplary embodiment of the invention.

Detailed Description of the Invention

It is to be understood that the present disclosure is not limited in its application to the details of construction and the arrangement of components set forth in the following description or illustrated in the drawings. The present disclosure is capable of other embodiments and of being practiced or of being carried out in various ways. In addition, it is to be understood that the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting.

The use of “including”, “comprising” or “having” and variations thereof herein is meant to encompass the items listed thereafter and equivalents thereof as well as additional items. The terms “a” and “an” herein do not denote a limitation of quantity, but rather denote the presence of at least one of the referenced items. Further, the use of terms “first”, “second”, and “third”, and the like, herein do not denote any order, quantity, or importance, but rather are used to distinguish one element from another.

The present invention provides a computer-implemented system and method for analyzing postcolonial trauma and gendered violence through literary narratives. The system is designed to assist scholars, educators, and researchers in systematically extracting, annotating, and interpreting literary representations of trauma and violence embedded within postcolonial texts.

In an embodiment, the system comprises an Input Module configured to receive digitized literary texts in formats such as PDF, DOCX, or TXT. The Input Module includes an intuitive user interface that allows users to upload texts individually or in batches. Alongside text upload, users can enter relevant metadata, including author name, publication year, geographical context, language, and genre. This metadata forms a foundational layer for subsequent thematic and comparative analyses within the system.

Once the text is ingested, it is directed to the Preprocessing Module. This module integrates natural language processing (NLP) functionalities such as tokenization, stop-word removal, lemmatization, and part-of-speech tagging. The Preprocessing Module further performs named entity recognition to identify and tag entities such as person names, locations, cultural references, and colonial institutions. Additionally, it extracts narrative features, including narrative voice (first-person, third-person), tense usage, and temporal markers, which are crucial in trauma analysis where temporal disruptions or narrative fragmentation often signify psychological distress.

The processed text is then analyzed by the Analysis Engine, which forms the core of the invention. The Analysis Engine includes a Trauma Theory Submodule embedded with lexicons and conceptual frameworks derived from established trauma studies literature. This submodule identifies textual representations of trauma, including dissociation, silence, fragmentation, flashbacks, and testimonial disruptions. For example, sentences indicating memory loss, temporal confusion, or unspoken trauma are flagged and annotated, enabling scholars to visualize trauma patterns within a narrative.

In parallel, the Gendered Violence Submodule within the Analysis Engine applies a taxonomy of gender-based violence to the processed text. This taxonomy categorizes violence representations into types such as sexual violence, domestic abuse, honor-based violence, and intersectional oppression, ensuring a nuanced understanding aligned with gender studies frameworks. The submodule uses curated dictionaries of gendered violence terminology and context-based phrase analysis to capture explicit and implicit references to such violence.

The Analysis Engine further comprises a Narrative Structure Analyzer that examines the broader narrative architecture of the text. This analyzer identifies narrative arcs, focalization shifts (shifts in narrative perspective), temporal distortions, metafictional interventions, and stream-of-consciousness passages. By mapping these structural elements, the system contextualizes trauma and gendered violence representations within the progression and design of the literary work.

All processed data, annotations, and thematic classifications generated by the Analysis Engine are stored in a Database Module. The database is structured to support efficient retrieval and comparative studies across multiple texts, authors, regions, and time periods. It stores both the original and annotated versions of the texts, along with metadata and analysis results, in relational tables linked to user profiles, enabling personalized data management.

The system also includes an Output Module, which generates comprehensive analysis reports and visualization outputs. The reports present annotated excerpts, trauma and violence classifications, frequency counts, and narrative structure summaries. The visualization outputs include heat maps depicting violence intensity across chapters, network graphs illustrating relationships between characters and trauma events, and timelines showing the progression of trauma and violence representations within the text. These outputs can be exported in formats such as PDF or CSV and are also accessible through an application programming interface (API) for integration with external research repositories or institutional digital archives.

In an exemplary embodiment, the system is implemented as a cloud-based web application, leveraging NLP libraries such as spaCy or NLTK for linguistic processing, a backend framework such as Django or Flask for server-side operations, and data visualization libraries such as D3.js for generating interactive graphs and maps. The database is preferably implemented using PostgreSQL with full-text search capabilities to ensure efficient data retrieval and analysis scalability.

The method of operation of the invention includes receiving the digitized literary text input along with metadata, preprocessing the text through the NLP pipelines, applying trauma theory lexicons and gendered violence taxonomies to identify and annotate relevant text segments, analyzing narrative structures to contextualize the identified themes, storing the annotated and analyzed data in the structured database, and generating thematic reports and visualizations for scholarly use.

Overall, the invention provides a structured, reproducible, and scalable approach for analyzing postcolonial trauma and gendered violence in literary narratives, integrating multiple interdisciplinary frameworks into a single automated system. It enhances the accuracy, depth, and efficiency of literary analysis, facilitating critical scholarship, pedagogical development, and digital archiving in humanities research.

Referring to figs. Fig.1 illustrates a schematic block diagram of the architecture of the system for analyzing postcolonial trauma and gendered violence within literary narratives. The diagram comprises an Input Module, which receives digitized literary texts and associated metadata, connected to a Preprocessing Module responsible for tokenization, lemmatization, stop-word removal, and linguistic feature extraction. The preprocessed data is fed into an Analysis Engine, which further includes three submodules: a Trauma Theory Submodule for identifying trauma-related representations, a Gendered Violence Submodule for classifying gender-based violence types, and a Narrative Structure Analyzer for examining narrative voice, focalization shifts, temporal distortions, and metafictional elements. The processed data is stored in a Database Module for structured storage and retrieval, while the Output Module generates thematic analysis reports and visualizations based on the analyzed data. The arrows indicate the data flow from input to output through the interconnected modules.

Fig.2 depicts the data flow diagram illustrating the process from text input to thematic analysis output. The diagram begins with Text Input, where digitized literary texts are received, and proceeds to Preprocessing, which cleans and linguistically processes the texts. Following preprocessing, data flows into the Analysis stage, which is divided into two branches: Postcolonial Trauma Analysis, where trauma-related representations are identified and annotated, and Gendered Violence Analysis, where gender-based violence representations are classified and tagged. The outputs from these two analytical branches converge into the final stage, Thematic Analysis Output, where comprehensive thematic reports and visualizations are generated for scholarly interpretation.

Fig. 3 shows a sample visualization output that depicts trauma and gendered violence mappings across multiple texts. The graph comprises two lines: a solid line representing postcolonial trauma and a dashed line representing gendered violence, plotted across four texts labeled Text 1 to Text 4 on the x-axis. The y-axis represents the intensity or frequency of identified representations. Data points are marked with circular symbols for trauma and square symbols for gendered violence. This visualization output enables comparative analysis of trauma and gendered violence representations across different literary texts, aiding scholars in identifying thematic trends, contrasts, and intersections within the corpus under study.

Fig. 4 illustrates the interface design for uploading texts and accessing analysis results within the system. The interface comprises an upper section labeled “Upload Texts,” which includes a drag-and-drop file upload area represented by a file icon and a “Browse…” button allowing manual file selection. Below a dividing line is the “Analysis Results” section, featuring three vertically aligned buttons labeled “Analysis Results 1,” “Analysis Results 2,” and “Analysis Results 3,” which provide access to the respective thematic analysis outputs generated by the system. The clean, minimalistic interface design ensures intuitive user experience for scholars uploading texts and retrieving analytical results.
, Claims:CLAIMS
We Claim:
1. A computer-implemented system for analysing postcolonial trauma and gendered violence within literary narratives, the system comprising:
a. an input module configured to receive digitized literary texts along with metadata;
b. a preprocessing module configured to perform tokenization, lemmatization, stop-word removal, part-of-speech tagging, and named entity recognition on the received texts;
c. an analysis engine comprising:
• a trauma theory submodule configured to identify and annotate textual representations of trauma based on integrated trauma lexicons;
• a gendered violence submodule configured to classify and annotate textual representations of gender-based violence using gendered violence taxonomies; and
• a narrative structure analyser configured to examine narrative features including narrative voice, focalization shifts, temporal distortions, and metafictional interventions;
d. a database module configured to store the processed texts, annotations, thematic classifications, and user-generated tags; and
e. an output module configured to generate thematic analysis reports and visualization outputs based on the processed and analysed data.

2. The system as claimed in claim 1, wherein the trauma theory submodule is further configured to identify literary representations of trauma including dissociation, silence, fragmentation, flashbacks, and testimonial disruptions.

3. The system as claimed in claim 1, wherein the gendered violence submodule is further configured to categorize violence representations into sexual violence, domestic abuse, honor-based violence, and intersectional oppression.
4. The system as claimed in claim 1, wherein the output module generates visualization outputs comprising heat maps of violence intensity, network graphs of character-trauma relationships, and timelines of trauma and violence progression within the text.

5. A method for analysing postcolonial trauma and gendered violence within literary narratives, the method comprising the steps of:
a. receiving digitized literary texts along with metadata through an input module;
b. preprocessing the texts by tokenizing, lemmatizing, removing stop words, performing part-of-speech tagging, and extracting named entities;
c. applying an analysis engine comprising trauma theory lexicons and gendered violence taxonomies to identify and annotate textual representations of trauma and gendered violence;
d. analysing narrative structures to contextualize the identified trauma and violence representations;
e. storing the annotated and analysed data in a database; and
f. generating thematic analysis reports and visualization outputs for scholarly interpretation.

6. The method as claimed in claim 5, wherein the step of analysing narrative structures includes identification of narrative arcs, focalization shifts, temporal distortions, and metafictional interventions.

7. The method as claimed in claim 5, wherein the thematic analysis reports are exportable in PDF or CSV formats and accessible via an application programming interface (API) for integration with external repositories.

8. The system as claimed in claim 1, wherein the preprocessing module further extracts temporal markers and regional dialect terms relevant to postcolonial analysis.
9. The system as claimed in claim 1, wherein the database module is configured to support comparative analyses across multiple texts, authors, regions, and time periods.

10. The method as claimed in claim 5, wherein the system is implemented as a cloud-based web application integrating natural language processing libraries, a relational database, and data visualization frameworks for interactive scholarly use.

6. DATE AND SIGNATURE

Dated this on 10th July, 2025
Signature

Mr. Srinivas Maddipati
(IN/PA 3124)
Agent for applicant