Abstract
This study aims to understand the feelings of newly converted Muslims when they narrated their pre- and post-conversion using the Machine Learning model and qualitative approach. The data set analyzed in this paper comes from in-depth interviews with 12 mualaf/ newly converted Muslims from various backgrounds. All recorded interviews were transcribed and filtered to remove any unnecessary or misaligned data to ensure that the data was fully aligned with the interview questions. To analyze emotional changes, we utilize natural language processing (NLP) algorithms, which enable us to extract and interpret emotional content from textual data sources, such as personal narratives. The analysis was performed in Google Colab and utilizing XLM-EMO, a fine-tuned multilingual emotion detection model that detects joy, anger, fear, and sadness emotions from text. The model was chosen because it supports Bahasa, as our interview was conducted in Bahasa. Furthermore, the model also has the best accuracy amongst its competitors, namely LS-EMO and UJ-Combi. The model also has great performance, with the overall average Macro-F1s for XLM-RoBERTa-large, XLM-RoBERTa-base, and XLM-Twitter-base are .86, .81, and .84. Furthermore, two psychologists compared emotion detection results from the XLM-EMO model to the raw input data, and an inductive content analysis was performed. This approach allowed us to identify the reasoning behind the emotions deemed pertinent and intriguing for our investigation. This study showed that Sadness is the most dominant emotion, constituting 46.67% of the total emotions in the pre-conversion context. On the other hand, joy emerges as the most dominant, constituting a substantial proportion of 57.73% among the emotions analyzed from post-conversion emotions data. Understanding the positive impact of religious conversion on emotions may inform mental health interventions and incorporate spiritual or religious elements into therapeutic approaches for individuals struggling with emotional issues, guiding individuals undergoing religious conversion and emphasizing the potential emotional benefits.
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