Meta-Analysis of Anita Desai’s Novels: A Comparative Study of Digital Humanities Tools for Topic Modelling

Digital Humanities, being an integration of computing and humanities, has transformed literary text analysis through the power of making textual analysis fast and accurate. The option of meta-analysis of an author's writings within a given time period has become possible. Researchers are now able to view the big picture and establish new relationships between a given novel and among all the novels of a specific writer, something that was not even feasible earlier. By using proper tools when analyzing data on the internet, researchers, particularly those from the department of humanities, are able to perform quality research without any fear of time deficiency or any fabricated data gathered. Topic modeling is also among the digital humanities tools that search over massive data to identify and compare underlying themes, stylistic and linguistic patterns, and narrative forms using computational approaches such as Latent Semantic Analysis (LSA). This paper is a comparison between MALLET (MAchine Learning for LanguagE Toolkit) and Orange, the two topic modeling packages. The two tools are compared based on ease of use and feature support in text mining for theme evaluation in the selected novels of Anita Desai, an Indian feminist writer. The input to be mined is the selected novels of Anita Desai. The paper examines how digital humanities tools like text mining, sentiment analysis, and word frequency analysis can be utilized by researchers to simplify the analysis process and make it more accurate. The objective of the research is to analyze Anita Desai’s novels to understand the predominant themes in her works. Subsequently, the findings of the paper suggest that MALLET software is more efficient than the Orange Data Mining Tool. By employing experimental methods in humanities research, this investigation presents an avenue for a unifying research partnership between computer scientists and humanities scholars.