Today marks the 2nd annual #BlueMind all-day meeting, held this year at The Romberg Tiburon Center for Environmental Studies, CA. The inaugural meeting was held at The California Academy of Sciences in San Francisco’s Golden Gate Park on early June, 2011.
As a former marine biologist, volunteer marine science and marine mammalogy instructor for The Marine Mammal Center in Sausalito, CA, longtime consulting statistician-applied mathematician, and currently working as founder and Chief Scientist at heur-e-ka, LLC, a small human-decision-making consulting firm and software outfit in San Mateo, CA seeking to take its 20+ year-old shrink-wrapped “semiotic-semantics“ offering to SaaS/PaaS world, I undertook to research, analyze, and ultimately test the veracity of the founding #Bluemind premise, conundrum, kōan;
“Why do we all feel better near the ocean, near water?”
While it’s clear to us all that some fear the water while others cannot splash around in it enough, #BueMind’s founding premise is a subtly complex invitation to multi-disciplinary participation in research into the neuroscience of humanity’s relationship with water. As evolved life-forms we literally owe our ancestry to the marine environment, perhaps most notoriously witnessed in the salinity of our own blood mirrored by the salinity of sea-water.
“Mother Ocean” appears to be a rather common cultural and spiritual notion throughout humanity’s natural history, a theme keenly reflected by the opening lines of “A Pirate Looks At Fotry” by the well-known folk-music star Jimmy Buffett.
Mother, mother ocean,
I have heard you call,
Wanted to sail upon your waters
since I was three feet tall. You’ve seen it all,
You’ve seen it all.
Here I present the findings form my analysis of sixty, randomly chosen “Ocean Stories“, random meaning the first 50 I could find and download via the Google query “ocean stories“. Obvious biases aside, like the relative frequency of
- adventure stories vs. love poems
- fiction vs. non-fiction
- commercially published vs. self= published authors
- 19th C. vs. 20th C.
- low sample-size (60) relative to the enormous bibliography of “ocean story” literature
…we feel our orignal premise that the emotional portent of “ocean words“ would be both bi-modal and dimensionally-significant, we pressed on. Our methodology was simple and fairly transparent.
- formulate oppositional emotion pairs (9) borrowing heavily from the work of;
- Richard Lazarus and his “cognitive emotion model” (Lazarus, Bernice N Passion and Reason: Making Sense of Our Emotions, 1994, Passion and reason: Making sense of our emotions New York: Oxofrd University Press).
- Paul Ekman’s classifications of basic emotions ( Ekman, P., & Friesen, W. (1971). Constants across cultures in the face and emotion. Journal of Personality and Social Psychology, 17(2), 124-129.).
- Robert Plutchik’s “wheel of emotions” (Plutchik , R. (2002). Nature of emotions. American Scientist,89, 349.) suggesting eight primary bipolar emotions: joy versus sadness; anger versus fear; trust versus disgust; and surprise versus anticipation.
- scrape the text from the top 60 “ocean stories” query to Google.
- analyze that text with Readware, the semiotic-semantics toolkit.
- Cluster each essay’s weighted output against the 9 selected emotion-pairs.
- Graph the frequency of the significant terms found and their aggregated, standardize valence (emotional strength).
There is much to see here (the length of the graphs indicate variation in terms of how much “term domination” [sheer vocabulary] of the emotional-dimension there is). The color indicates the overall strength of the emotional valence at work.
While I’ve not labeled the “emotions“, per se’, I’ve allowed their lexical anchors to represent each emotional dimension’s content for some interpretative flexibly (and less theoretical hubris on my part). Note the radial, 180-degree opposition of the 9 emotional-dimensions, done purposely to dramatize the effect.
The strength (valence) is all in the “tails” (color), which bears out the bi-modality of emotion theory I’ve had all along. There is not a lot of “half-way” in the way people speak about emotions in general, and particularly so regarding the ocean.
So, here we see, in the context of terms authors use to describe their relationship with the ocean;
more mean than kind
more needy than giving
more loving than hateful
more suspicion than trust
more calm than excited
more humility than pride
Interestingly, happy and sad essentially equate!
We are pleased by the results despite understanding a host of changes face us as we work out some daunting sampling issues; ranging from topical bias, utterly inadequate estimates of the population’s multivariate distribution, and the number and subsequent ranges of term-to-emotion variance inherent to “ocean literature“.
But an over-arching and superior chord has been struck and proven; dynamically generated topics and emotions are far more analytically true, inferentially useful, and naturally representative of human cognitive processing than the highly artificial and all too often superficial results that emante from “NLP-centric pairwise keyword classifiers” and their concomitant “static and low-association sentiment synonyms”
Here are the 60 “ocean stories” analyzed;