In December we asked on twitter ‘what words come to mind when thinking about 2010′ (we took out a few inappropriate ones).

We don’t know how representative it is. Actually we can assume it isn’t representative – we think it was a small-ish sample of people we knew on Twitter participating, but could have been anyone who got the link to the survey.

One could say that the general consensus about 2010  from this group was:

- long hard crap year with awful wikileaks but a growth in connections; or

- wikileaks caused chaotic and crazy reflection of connections, depressing long hard  GFC recovery growth.

At Tribe Research, 2010 saw a lot of change and some putting of wheels-in-motion for 2011. In the next few weeks we’ll be rolling out a key aspect of our activity in 2010 - improvements to the CloudMaker and ActionMap components of  Tribal Tool-Kit.

And here is what you thought about 2011…

We hope at the end of 2011 you’re not thinking – long hard crap as your top 3 descriptive words, but we do hope growth and connections are! We also hope that floods and disaster don’t remain as the key words for 2011 but hope, new and love do.

International sporting events such as the Commonwealth Games and the Olympic Games are often used by host countries to highlight their positive attributes, which in turn are meant to increase trade and tourism. To do this they often wow us with opening ceremonies, amaze us with carefully crafted cultural stories, and persuade us with the experiences of the thousands of people who attend the events.

Unfortunately, with the high demands of modern media networks, minor errors start to appear as major ones, and major errors appear as a total debacles. Thus trying to win over an audience in this environment is extremely difficult.

Interested in how well the organisers had done so far in promoting India, we asked Twitter and Facebook their reaction to the Delhi 2010 Commonwealth games via one simple question…

“When you think about the Delhi2010 Games, what is the first word that comes to mind?”

And this was the result….

While the result offer interesting insights into the minds of the people who have completed the survey, it is important to highlight a few characteristics of this survey that have impacted the result and possibly impact the way it should be perceived.

1. Number of survey participants

Having done a brief search (finding channel 10 data on Australian TV Watching Community- Throng site) on viewer-ship  of the Commonwealth games “Day 1″, I discovered that between 670,000 and 1.3 million people had seen various events through out the day. This suggests that the 66 people who took part in the survey may not provide the best overall representative reaction to the games. This result  is however still representative of the group of people who took part and representative of part of our tribe.

2. Frequency of words

Asking survey respondents to only give one word means the chance of getting a wide range of frequencies is much less than it would be if we asked for three words from each respondent. Tribal Tool-Kit mini survey allows you to choose one, two or three words to enter. This time we chose only one word to force people to put more thought into their response, honing it into something more valuable. Tribal Tool-Kit also allows cleaning of results to avoid typos, and completely meaningless responses, though we did not use the feature this time.

So what is the overall result?

While this survey is just a bit of fun, it does suggest to me that while Australian’s think the games are a “boring” “shambles” verging on “chaos”, we still enjoy winning “gold”.

Want to try you hand at setting up your own survey. Why not sign-up and give it a go…

A CloudMaker mini survey example

We were curious about the words people on social media use when they think about the skills needed in business. So, we developed a CloudMaker mini survey.

When you think of the skills needed in business, what first 3 words come to mind?

Here are the results, while we don’t know the sample, it is still an interesting set of words to think about.

What are the first 3 words that come to your mind?

A CloudMaker mini survey example

If your tribe is using different words to those you use, then there is a disconnect in the message people are receiving about your organisation.

When you think of us, what are the first 3 words that come to mind?

Tribe Research did this and developed our cloud.

This simple activity that takes almost no time, allows you to find out the language they use when they talk about your organisation. If your marketing uses different words to what you are using, there is a disconnect and people are getting mixed messages.

Does your tribe use the same words as you?

Have you recently checked your website has the message you want?

It can be the first place prospects see you, so you want make sure it’s sending the right message.

This quick check will make sure they get the right message

Just reading your website is a good way to start. Check consistency of phrasing between the website and what you say when you talk about your business, as it might’ve changed since you wrote the website copy.

Most people scan a website, jumping across words, so a great way to check the message of your website is to have a list of the words, ordered by frequency. Are the most common words the ones you want people to remember? Are there any typos in the list?

Here is a simple way to check the words on a website page using CloudMaker in Tribal Tool-Kit:

1. Login to Tribal Tool-Kit. You can easily create an account if you don’t have one. You get 3 credits for CloudMaker and this only uses 1, so the check is free.
2. Click on in the red banner along the top.
3. Click on in the gray menu on the left.
4. Fill in the form with:
   • The name of your business
   • Your website address
   • Change the 4 next to “Minimum word length” to 1 (then all words are loaded into Tribal Tool-Kit and you can see if you have too many small joining words making your website difficult to read).
   • Click “Get Page Words”
5. You are told whether the page loaded successfully or not. The first line will tell you how many words have been retrieved from your website. Click “Accept Dataset”.
6. You will see a table with the words and their frequency. The most frequent at the top.

Readers of your site will leave remembering prominent words. Make sure they are the ones you want them to have.

CloudMaker feature explained

How to create a hyperlinked word cloud to place on a webpage, so that when the words are clicked they take you to a specific website page. An explanation of word clouds is on the CloudMaker webpage.

Case study on North Side Coffee Mornings

Tony Cosentino started a guest book of people attending North Side Coffee Mornings (NSCM or #NCSM) that he has been posting to the North Side Coffee Mornings Posterous site. He wanted to create a word cloud of the people who have come along so the more often they have been to NSCM the larger their name is.

Before he got started we had a bit of a chat, the napkin shows our discussion about it.

Firstly, he set up a spreadsheet with the following format:

• A : Twitter name (eg: @katetribe).
• B : Formula of the sum of columns D, E, F, G etc.
• C : Website address for the twitter name (eg: http://www.twitter.com/katetribe).
• D : Date 1, then column E is date 2, etc. If a person attended an NSCM then they had a 1 put in cell for the dates they attended.

Secondly, the formula column B needs to be copied then paste special with only the values pasted (remember to not save the spreadsheet file as you will then loose the formulas). Then delete the date columns.

Thirdly, save the file with the 3 columns and no column headings as a csv.

Then it is time to play with CloudMaker in Tribal Tool-Kit.

• Click on Upload to CloudMaker.
• The title in this example is: NSCM Guestbook the last 6 weeks…
• The description in this example is: All guestbook data between 29 October 2009 and 3 December 2009.
• Select the file and then click upload.
• As the spreadsheet in this case is already edited there is no need to use the CloudMaker editing features.
• Click on Create word cloud from dataset.
• In the display options section change, Show HTML source to ‘yes’.
• Click ‘re-draw word cloud’ at the bottom of the screen.

Finally, copy the HTML code and paste it into the webpage you would like it to appear.

The outcome: The CloudMaker word cloud below is also on the Posterous site. They look slightly different due to website styling on each site.

Easy isn’t it! Now other coffee mornings (as well as other events) can start a guest book from the start so that they can progressively create their own word clouds.

Word clouds from Facebook Fan Pages

The Mocks fan page is very active, so I thought it would be interesting to create a word cloud of the comments from: What kind of weekend did you and your Mock have – in one word?

Some comments had a little story, and we still included these.

This is what we did to get the word cloud below:

• Copy and pasted the text into a spreadsheet
• Deleted the profile pic, time and ‘comment’. This left the comments.
• Did a few find & replaces.
  • Took out all the symbols by finding . , ) [ ! etc and replacing with nothing
  • To find spaces and replace with comma and space. This allows CloudMaker to make a series of words into separate words for the word cloud.
• Saved as a CSV file.
• Uploaded the CSV to Tribal Tool-Kit.
• Clicked on the ‘Amalgamate similar terms’ link (this will merge the same words so your words are easier to edit).
• Added a list of words to the stopword list. These were: i; my; to; and; the; a; are; comment; dont; for; im; in; it; of; they; still; is; come; with. This means that these words were still in the list of data, but won’t appear in the word cloud.
• Deleted from the list: don’t
• Merged some words that were similar so that they had a higher frequency and therefore appeared bigger:
  • Supercalifragilisticexpialidocious and supercalifragolisticexpialidociousi
  • BORING and boringi
  • disappointing and disappoint
  • Mockariffic and Mockorific
  • Mocktastic and mocktasstic
• Clicked on ‘Create word cloud from dataset’.
• Changed the font to: Comic Sans MS (Bold Regular).
• Changed ‘Convert case’ to ‘all lower case’
• Made the maximum frequency colour black (#000000)
• Made the minimum frequency colour pink (#CC3399)
• Changed the ‘Save options and formatting’ to ‘new template’
• Clicked on ‘re-draw Word Cloud’
• Gave the template the name ‘Mocks’ and clicked ‘Save’. There is an option to make the settings the default template so future word clouds have this format as soon as you click on the ‘Create word cloud from dataset’.
• Then clicked on ‘Save as image options’. You can save the word cloud as an SVG, PNG, or JPEG image format. JPEG is the lowest quality but opens in the most applications. The word cloud to the right is a JPEG format.

Simple. And interesting. Lipgloss is so big because we kept the 3 times it was said in the one comment shown above. Great to see the number of ways that fans put ‘mock’ into a word and that ‘supercalifragilisticexpialidocious’ was used more than once!

Scenario: You have done a survey and you want to get a quick understanding of the words participants used to answer an open response question.

Solution: A perfect way to do this is to make a word cloud – a visual way to understand the frequency of words; where words with a higher frequency are larger, and words with a lower frequency are smaller.

Problem: The English language has two main spelling systems – the British system and the American system. Read more about the differences at Wikipedia.

Implication: The two spelling systems result in a lower overall frequency for essentially the same word, as they are considered 2 words, and therefore a smaller size in a word cloud.

For example, localise and localize are the same word. If each are used 5 times by participants, the two words would be smaller than if they were combined to have a frequency of 10 using the spelling of your preference.

To show the impact this has on a word cloud, I selected a group of words with different spelling and put them into a spreadsheet. To create a frequency, I used a formula to count the number of characters in the word [In Excel this is LEN(text)].

Most word cloud software only allows you to paste in a group of words or upload a file of words, before generating the cloud. You can sometimes automatically merge similar words (for example when there is the word, the plural, and end with ‘ing’ they will merge to be one word with the combined frequency). I haven’t found one, other than CloudMaker, that allows you to personally merge similar words, enabling you to handle the problem of British and American English.

Below, the first word cloud is all the words and to the second word cloud is the merged list.

Fewer words makes it easier to understand but also changes the priorities.

All the words

Merged words

Impact: When words with British and American spelling are mixed with words spelt the same in both systems, the first impression views could be inaccurate.

For example, if there was a single spelt word, such as: national, with the frequency of 10 and one of the dual spelt words, such as: localise with the frequency of 7, then also localize with a frequency of 5, merging localise and localize results in a frequency of 12, which is greater than the single spelt word, national, with a frequency of 10.

This could change your thinking about how the question was answered as localise is more frequent than national.

If the question was: What should our regional focus be? Then merging the British and American systems would result in a different first view, than looking at a word cloud without merging – because localise would be greater than national rather than the reverse when not merged.