Semantic Clustering for Nomenclature Purposes

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A bit of an idea on how to better capture meaning and semantic relationships within domains. Digitally slanted but could be applied from everything from a nomenclature task to engagement strategies.

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  • Thanks for the link, Drew!!
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  • Hi Drew,

    Awesome feedback! Thanks! I have long since given up on any idea of mine being 'new' so no worries there. This is very much a half-baked idea and I really appreciate the feedback! I was utterly unfamiliar with these IBM products.

    I am familiar with a large number of card sorting approaches that are closed systems. As I'm unable to find anything detailed on the IBM products (please send links if anyone finds some), I am running with the potentially erroneous assumption that they were sorting exercises in nature, vs. emergent insight into the domain's scope, size or meaning.

    Don't take me wrong. I hold nothing against sorting exercises as a secondary task. I was rather exploring the option to generate free associations so as to allow visitors to define the domain. Much more like a 2003 free listing exercise proposed on boxes and arrows: http://www.boxesandarrows.com/view/beyond_cardsorting_free_listing_methods_to_explore_user_categorizations

    Only, unlike free listing, we maintain some links (relationships) from which to search for clues to 'meaning', if you will.

    My idea was just one way to automate the collection of this data that seemed simple, straight forward and even fun for users to participate in.
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  • Thanks Debs!
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  • love this - thanks for posting!
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  • slide 29 should read 'One appears to relate stronger to financial presentations in a corporate environment.'
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Semantic Clustering for Nomenclature Purposes

  1. 1. Semantic Clustering for Nomenclature Purposes by Sean Howard
  2. 2. A very smart man Matthew Milan: http://tinyurl.com/3nklu8
  3. 3. A very smart man recently said, “In the last five years, I can't identify a single original method that has grown up inside the IA field.” “It's time to seriously invest in a new set of tools, and we're going to need to build some of them from scratch.” Matthew Milan: http://tinyurl.com/3nklu8
  4. 4. which got me thinking MEANING and how we struggle about RELATIONSHIPS with defining VALUE that bring to a domain
  5. 5. or more specifically NOMENCLATURE
  6. 6. Every UX job generally involves a nomenclature review, refinement or overhaul at some point or another How do we come up with our final recommendations?
  7. 7. I know a firm that hires a third party semiotician to define the value and meaning relationships for a project A black box solution, if you will Image Source: Mr. Noded, http://flickr.com/photos/jrnoded/
  8. 8. The rest of us tend to use brainstorm thesaurus card sort content theft etc. audit Image Source: Jacob Bøtter, http://www.flickr.com/photos/jakecaptive/
  9. 9. not to mention a stiff drink (or three)
  10. 10. and then we test, refine and repeat
  11. 11. What if there was a better way to identify semantic relationships with our actual audience?
  12. 12. What if there was a better way more MEANINGFUL to identify semantic relationships with nomenclature our actual audience?
  13. 13. What if we could build a map of meaning and explore proximity by association to better understand our audiences? For more information: Semantic Memory: http://en.wikipedia.org/wiki/Semantic_memory Priming: http://en.wikipedia.org/wiki/Priming_(psychology)
  14. 14. I give you: a semantic mapping tool
  15. 15. Here we see sample results in aggregate showing potential meaningful relationships held in common for one term Term: Consumer 82 68 58 42 Marketing 34 Product Person Fallacy Goods This could be further segmented by a number of other factors (demographic, psychographic, etc.)
  16. 16. Not everyone types at the same speed. Let’s define the avg. time to enter a word* from first keypress to last keypress as tkey tkey is 1.34 seconds * A word being defined by the act of the user pressing the submit button.
  17. 17. tthink can then be total time minus tkey where tthink can then be used to define those words that come quickest/easiest tthink tkey total time from presentation of word to submission of word by the user Note: deleting of the letters and starting over likely needs to be taken into account as well
  18. 18. We may want to segment clusters based on a factor of tthink (those that came to your audience quickest.) Term: Consumer 82 < 1.25 sec 68 < 2.50 sec 58 > 2.50 sec 42 Marketing 34 Product Person Fallacy Goods
  19. 19. Or alternatively, show words as nodes in a network diagram where the length of the line is the average speed to come up with the word. Product Term: Consumer Fallacy Person Goods Marketing There may also be value in the order in which words are entered.
  20. 20. This is about building a better understanding of the language and meanings pertinent to the stakeholders within a domain
  21. 21. I ran a simplified version of this experiment with three friends
  22. 22. I ran a simplified version of this experiment with three friends money hat Financials suit market bank account
  23. 23. I ran a simplified version of this experiment with three friends measurements charts company CFO Financials spreadsheets pale green projections
  24. 24. I ran a simplified version of this experiment with three friends corporate results Financials investing annual reports brownies
  25. 25. Two of my subjects show signs of a more personal relationship with “financials”
  26. 26. Two of my subjects show signs of a more personal relationship with “financials” One appears to relate stronger to financial presentations
  27. 27. Two of my subjects show signs of a more personal relationship with “financials” One appears to relate stronger to financial presentations The terms “hat”, “pale green” and “brownies” are some of the areas I would be curious to explore further Ann did mention being hungry during the experiment.
  28. 28. greater INSIGHT
  29. 29. Enabling us to create better content, define stronger navigation, and better connect with our audience
  30. 30. Anyone want to build this? Go for it. This work is licensed under the Creative Commons Attribution 2.5 Canada License. To view a copy of this license, visit http://creativecommons.org/licenses/by/2.5/ca/ Questions or Comments? Find me at: http://www.craphammer.ca/

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