Storytelling analysis interactive tutorial

You searched for all stories that contained the words listed under "selected filters" below. This retrieved 300 stories.

How to interpret the icons:
Narrowing your search from slum to "kibera slum" using quotes reveals hundreds of stories. If you mouse over the picture of the young man, you'll see that 54% of all stories were told by this demographic group.

Trends
(Benchmarked against all stories we've ever collected)

Demographics

Topics

Responses
(within this story collection, not benchmarked)

Total Processing time: 1.0 seconds
Processing messages:

*** RANDOM story conditions ***
Found 300 records.
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A[pADAnXJXKqyE]:SUCCESS: 1 rows inserted.

TOP ANSWERS:The right people,Inspired,Good idea that succeeded: 2770
--- The right people,Happy,Good idea that succeeded: 2135
--- The right people,Important,Good idea that succeeded: 1539
--- The right people,Hopeful,Good idea that succeeded: 1244
--- The wrong people,Important,Good idea that succeeded: 203
--- The right people,Hopeful,Good idea that worked somewhat: 169
[]
Benchmark processing time:0.96s

Stories

(Narratives and answers to any associated survey questions)

Why use benchmarks?
By now you probably noticed that the size and color of icons are pre-adjusted or "benchmarked" against a reference data point. By default the reference is "all other data we've ever collected" but you can customize that benchmark to be something specific and logical to your question.

Benchmarks are important! This is what raw data from a typical collection would look like without benchmarking:

First, everything is green. People are 10 to 20 times more likely to be positive in stories than negative, depending on how they were prompted. Second, the results now emphasize the unevenness of the sample across age and gender. Like the positive story bias, this uneven sample is nearly always present in data. Instead of throwing out all of the data, we display results weighted against a large reference sample, so that any collection of randomly selected stories will look like this:

Every icon is yellow (neutral) and medium-sized, because they are a representative sample. If you asked 100 people to participate, this would be the breakdown of who responds, based on asking over 60,000 people so far. But if you wanted the benchmark to be 100% women, you can select that with "compare" tool, explained later.

Using quotes to search for phrases

You searched for "kibera slum".

Notice that putting quotes around two words narrows the number of stories that appear in your collection. However, a more powerful and flexible way to search for stories is you put a bunch of words inside parentheses, like ("kibera slum" "mathare slum") and (housing house home) instead of None.

The search engine will include stories that have any one of these words inside the parentheses.

Try searching for

("kibera slum" "mathare slum") and (housing house home)

by typing it into the search box as shown:

You searched for all stories that contained the words listed under "selected filters" below. This retrieved 300 stories.

Trends
(Benchmarked against all stories we've ever collected)

Responses
(within this story collection, not benchmarked)

Percent of stories matching each answer
(This mini table allows you to compare frequencies with REF: the percent who gave this answer in all stories)

Diversity of data sources

Stories

("kibera slum" "mathare slum") and (housing house home)

You searched for all stories that contained the words listed under "selected filters" below. This retrieved 300 stories.

Trends(Benchmarked against all stories we've ever collected)

Responses (within this story collection, not benchmarked)

Percent of stories matching each answer (This mini table allows you to compare frequencies with REF: the percent who gave this answer in all stories)

Diversity of data sources

Stories Show

("kibera slum" "mathare slum") and (housing house home)

Trends
(Benchmarked against all stories we've ever collected)

Responses
(within this story collection, not benchmarked)

Percent of stories matching each answer
(This mini table allows you to compare frequencies with REF: the percent who gave this answer in all stories)

Stories