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Religious Scripture Text Analytics
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About
This dataset provides a focused resource for text analysis and sentiment analysis applied to foundational religious texts: the King James Version (KJV) of the Bible and the Quran. It offers an opportunity to explore linguistic patterns, emotional tones, and thematic structures within these significant historical and spiritual documents. The dataset is particularly useful for researchers and developers working on natural language processing (NLP) tasks, allowing for the extraction of valuable insights from unstructured text data and deeper understanding of these widely studied scriptures. It supports various text mining applications, including sentiment polarity detection and identification of key concepts.
Columns
The dataset is structured to facilitate detailed text analysis. While specific column names for the CSV files are not provided, typical columns for this type of sentiment analysis and NLP dataset would include:
- text: The original passage or verse from either the King James Version of the Bible or the English Quran.
- sentiment_score: A numerical score or category representing the emotional tone (e.g., positive, negative, neutral, or specific emotions like joy, anger, fear) derived from sentiment analysis techniques like Bing or NRC.
- source_text: An identifier indicating whether the text originates from the KJV Bible or the Quran.
- tokenised_words: Individual words or tokens extracted after processing the original text.
- part_of_speech: The grammatical role of each word (e.g., noun, verb, adjective).
- named_entities: Recognised entities like people, organisations, or locations mentioned in the text.
- word_count: The total number of words in a given text segment.
Distribution
The dataset is primarily distributed as two CSV files:
Old_Testament_KJ_Bible.csv and Quran_english.csv, designed for straightforward integration into data analysis workflows. Additionally, a Markdown document containing R code for visualisations is included, allowing users to reproduce and extend analytical insights. Specific numbers for rows or records are not available at this time. The data files are typically in CSV format and can be updated separately on the platform.Usage
This dataset is ideally suited for a variety of analytical and research purposes, including:
- Natural Language Processing (NLP) Research: Developing and testing new text analysis algorithms, especially for sentiment analysis, topic modelling, and text classification on religious or historical texts.
- Academic and Theological Studies: Gaining data-driven insights into the linguistic and emotional characteristics of the Bible and Quran.
- Artificial Intelligence and Machine Learning Development: Training language models or AI systems that require diverse text data, particularly in the domain of spiritual or historical literature.
- Linguistic Analysis: Exploring lexical diversity, word frequencies, and semantic relationships within sacred texts.
- Visualisation Projects: Creating word clouds, sentiment timelines, or other visual representations of the textual content.
Coverage
The dataset's scope is primarily textual, covering the King James Version of the Bible and the English translation of the Quran.
- Geographic Scope: Although the texts originated in specific regions, their influence and study are global.
- Time Range: The texts represent historical periods, with the KJV commissioned in 1604 and published in 1611, and the Quran revealed from 610 CE onwards and compiled around 650 CE.
- Demographic Scope: The content is relevant to studies concerning Christianity and Islam, influencing billions worldwide. Data availability is focused on the provided
Old_Testament_KJ_Bible.csvandQuran_english.csvfiles.
License
CC0
Who Can Use It
This dataset is valuable for:
- Data Scientists and Analysts: For conducting sentiment analysis, text mining, and statistical analysis on large textual datasets.
- NLP Researchers and Engineers: For training and evaluating NLP models, especially in the context of historical or religious texts.
- Academics and Students: In fields such as theology, religious studies, linguistics, and digital humanities for research and coursework.
- AI/ML Developers: For creating applications that require understanding and processing textual content from a spiritual context.
- Content Creators and Journalists: For generating insights or visualisations related to religious texts for articles or media projects.
Dataset Name Suggestions
- Sacred Texts Sentiment Analysis
- Religious Scripture Text Analytics
- KJV Bible and Quran NLP Dataset
- Historical Religious Text Sentiment
- Scriptural Sentiment Insights
Attributes
Original Data Source: The Bible and The Quran: Sentiment Analysis.
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