JFK Document Files Textual Analysis

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JFK Document Files Textual Analysis

A Temporal Corpus for Exploring 2017 Release

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About this dataset

This dataset is a record of text-based documents related to the 2017 release of files associated with the JFK case. It provides an invaluable source of textual information to enable temporal analysis, by extracting texts from the PDFs and compiling it into one structured corpus. This corpus reveals a multitude of insights that can be explored, such as differences in documents over time and polarization shifts within various documents. By taking advantage of this dataset, researchers have access to valuable primary sources allowing them to investigate facts, ideologies and perceptions around the JFK case with increased clarity. Dive deep into history using this collection as your guiding light!

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How to use the dataset

This dataset is an invaluable source of textual information for analyzing the 2017 release of documents related to the JFK case. It provides a structured corpus composed of full-text content from PDFs released in 2017, making it an excellent tool for uncovering interesting patterns and insights about the contents of this collection.

In this guide, we’ll go over some tips on how to get started with text analysis of this dataset.

1. Get familiar with your data: Before you start your analysis, take a look at what types of content are included in the text files and become familiar with its structure and format. A quick glance will give you an overall understanding of what types topics are discussed in each document that can help inform your further analysis steps.

**2. Explore topic modeling: ** Topic modeling is an unsupervised machine learning technique used to explore topical trends within large document collections like this one provided by the JFK Document Files dataset by clustering documents together based on their respective contents and keywords. Once grouped together, topics can then be analyzed for which words correlate strongly to each other giving insight into emergent themes or phenomena related to a particular topic or collection as whole encompassing multiple topics or entities simultaneously without manual labor intensively reading through entire datasets up front to generate hypotheses or draw connections between various elements contained within them manually from scratch.. Topic models can also help identify any redundancies that exists between terms present throughout different bodies texts as way finding ways collapse higher order concepts into much smaller pieces thus creating more manageable analytics projects faster than otherwise could have been accomplished using traditional methods alone (e g scanning through individual files looking larger patterns).

 We recommend exploring software tools such as Gensim's Python libraries Latent Dirichlet Allocation (LDA), Non-Negative Matrix Factorization (NMF) etc if interested tacking natural langauge processing NLP projects in context where exploratory/unsupervised machine learning algorithms applications might be best suited present situation 

3 Identify meaningful clusters : analysing different clusters generated via topic modelling method , each one containing specific groupings corresponding words that frequently co occur said particular 'topic This type cluster discovery allows users quickly identify key topics any given corpora highlight emergent properties not visible until undergoing such process separating out these distinct categories ultimately yielding new perspective other insights relating those found within overall datasets themselves After obtaining targeted results practice refine thru noting which individual terms associated particularly closely given ‘group’ article excerpts then determine most salient concepts capturing

Research Ideas

• Analyzing the tone and sentiment of documents released over time to evaluate changes in public opinion on the JFK case.
• Creating a timeline visualization of document releases to observe any patterns in the documents’ content, publication dates or organizations involved in the release.
• Performing keyword searching within documents to identify recurring topics or key figures over time and observe their evolution throughout different periods of time related to the JFK case

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: documents.csv

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit .