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Word Cloud

Mauro Lupi
Robert Johnson
mlanders
andyvdg
Isman Tanuri
+44
  • Mauro Lupi
    Mauro Lupi
  • Robert Johnson
    Robert Johnson
  • mlanders
    mlanders
  • andyvdg
    andyvdg
  • Isman Tanuri
    Isman Tanuri
  • Alan Heckman
    Alan Heckman
  • mhoffman
  • Peter Green
    Peter Green
  • Thinkqualitative
    Thinkqualitative
  • Brian McCarthy
  • Rolf
  • Dana Prives
  • Jennifer DuHamel
  • Bernice Wong
  • Marieke
  • Kim Roth Howe
    Kim Roth Howe
  • Tim Dekkers
  • Innovatielab P-Direkt
  • Emily Reid
  • Bogdan Maran
  • Alisa Oyler
  • Charlotte Marmet
  • Sondra Reis
  • McAlinden Consulting
  • Renee Rubin Ross
  • Erin Foltz
  • Joppe
  • Eve Binder
  • Simon.Harris
    Simon.Harris
  • MICAELA VIEGAS DOMINA
  • Robert Rietveld
  • Ryan Wagner
  • Barbara Sedlack
    Barbara Sedlack
  • Ray Collis
  • Rachaelt
  • Jaakko Luomaranta
  • Puneet Chhikara
  • Fredrik Wendt
    Fredrik Wendt
  • Hannah Härtwich
  • Felix Boudreault
  • Jeremy Myers
  • Curtis Blackwell
  • Christian Gründler
  • Norro
  • Naureka
  • cravr
  • Siobhan McCarthy
  • QMS
  • Sami Nikander

I’ve seen some messages about this but joining in - would love to see a word cloud feature. I do workshops for clients to understand their brand better. We usually end up with about 100-500 stickies. It would be great to have an option to select either all of the stickies or the relevant ones and to see a word cloud generated to see what the rising themes are. 

 

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6 replies

Henrik Ståhl
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@Tamar Levy This is a great idea! 🌟 Question: Do you think all text should be extracted from the sticky notes and analyzed word by word? I'm thinking that the word cloud would consist of both single words and entire sentences otherwise.


Kiron Bondale
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  • Volunteer Community Moderator
  • 3040 replies
  • March 15, 2022

@Max Harper -

What do you think? Is this something which Clusterizer coiuld be extended to handle?

Kiron


Henrik Ståhl
Forum|alt.badge.img+7

Good idea @Kiron Bondale! I actually thought of Clusterizer when I started reading the post, but when I saw the visual example I figured it doesn't support that kind of visualization. Adding it as a feature in Clusterizer would definitely be worth a couple of coffees through Ko-fi. 😁😇


  • Author
  • Beginner
  • 2 replies
  • March 15, 2022

I think word by word (being sensitive to filler words) could work. Maybe even sensitivity to words like innovation// innovative, professional/ professionalism etc. to allow for more clusterization of variations of the same word. And yes, I agree it could be sets of words vs. individual words :relaxed:


Henrik Ståhl
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@Tamar Levy Having some sort of sensitivity sounds like a good idea!


Barry Smith

This would be an incredible feature. If as we are ideating we could do a +1 on anything posted (yes, too many stickies) that could help prioritize popular ideas. Going to start playing with Clusterizer!


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