Nursing Ghost Stories as told through Natural Language Processing
Language comes natural and easy to humans but is difficult for machines because of its structure and ambiguity. Ghost stories perhaps showcase that ambiguity as paranormal experiences are difficult to reconcile or explain within known scientific principles or inferences
Natural Language Processing (NLP) is a field of computing that enables computers to analyze, understand and communicate human language. Today natural language processing powers several technologies such as: speech recognition assistants; language translation; sentiment analysis; entity and relationship recognition; as well as text summation, parsing and analysis
The Natural Language Toolkit (NLTK) is a platform of libraries and programs for natural language processing written in the Python programming language. NLTK was developed at the University of Pennsylvania and first released in 2001
Word clouds are visual representations of a text, where the sizing of words displayed reflects their prominence or emphasis within the text. The word cloud application used here was developed with NLTK and other Python modules
Word clouds provide high-level analysis of themes associated with a corpora (body) of text. In business, they can be used to highlight pain points from customer feedback. For this effort, word clouds were applied to a collection of ghost experiences as told by nurses
Allnurses.com hosts a long-running discussion thread called “Nursing Ghost Stories” (NGS). The NGS collection spans over a decade (2005-2017) amounting to 199 pages as of the time of this writing. The NGS archive contains a mixture of first and second hand accounts along with commentary
Two corpora were developed from the NGS collection. One corpus contained plain text and another corpus was tokenized (tagged) by sentences, words and parts of speech. A word cloud was subsequently generated from the plain text corpus that is displayed above. Common stop words, for example prepositions were filtered out prior to the generation of the display
The word cloud is interesting for what it does and does not emphasize. For example, the words ghosts and hauntings along with their roots or extensions are not prominent in the display. Hauntings involve recurrent paranormal experiences commonly experienced in the form of ‘imitative noises” and in more elevated forms through apparitions. Many NGS discussions appear to involve sensed presence experiences
There also appears to be substantive emphasis on nearing death awareness (NDA) type experiences as said or told by patients, many of whom were in long-term care or hospice settings, to nurses under their supervision. In their final phases, terminally-ill patients often perceive welcoming apparitions or visitations from deceased relatives or loved ones. In NDA experiences, patients often appear to hold conversations with persons who are not physically present
As would be expected, terms of reference associated with medical profession are most prominent in the word cloud, however these terms could be filtered from future word clouds to potentially obtain deeper insights on the experiences
In the near-term, NGS corpora can be used to develop sentiment analysis. Also worth exploring are word pairings and conditional frequencies connected with them. A longer term effort would mix natural language processing with machine learning to characterize types of encounters within the NGS collection
Bird, S., Klein, E., & Loper, E. (2009). Natural language processing with Python: analyzing text with the natural language toolkit. “ O’Reilly Media, Inc.”.
Kircher, P. and Callanan, M. (2017, Dec 14). NDEs and Nearing Death Awareness in the Terminally Ill. International Studies for Near Death Studies (IANDS).
Natural Language Toolkit: NLTK 3.2.5 documentation. (2017, Sep 24). NLTK Project
Pearson, P. (2014). Opening Heaven’s Door: What the Dying May be Trying to Tell Us about where They’re Going. Random House Canada. Sponsored
What’s Your Best Nursing Ghost Story? (2017, Oct 30). AllNurses.com
Wordcloud from NGS Corpus. (2018, Feb 19). © Maryland Paranormal Research ®. All rights reserved.