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7 angles for
data stories
@PaulBradshaw
Birmingham City University, BBC Data Unit
https://leanpub.com/u/paulbradshaw
https://onlinejournalismblog.com/
https://gender-pay-gap.service.gov.uk/
https://gender-pay-gap.service.gov.uk/
https://onlinejournalismblog.com/2020/08/11/here-are-the-7-types-of-stories-most-often-found-in-data/
https://onlinejournalismblog.com/2020/08/11/here-are-the-7-types-of-stories-most-often-found-in-data/
Challenge 1: take a dataset and
see how many story ideas you
can list using the story
categories
Scenario: new rail
usage figures come
out - what stories
could you tell?
https://dataportal.orr.gov.uk/statistics/usage/estimates-of-station-usage
https://dataportal.orr.gov.uk/statistics/usage/estimates-of-station-usage
https://dataportal.orr.gov.uk/statistics/usage/estimates-of-station-usage
● Station name
● Station owner and group
● Region (and other area categories)
● Lat-long
● Entries & exits by type (full price,
reduced, season ticket, total)
● Previous year’s entries & exits
● Percentage change year on year
● Ranking
● Interchanges (not exit)
● Comments (e.g. engineering works)
https://docs.google.com/document/d/1QSX7IN2oOzGFsrwF-mL_04F5ANyvkHWixfrOZPa7xsg/edit?usp=sharing
What did you come up with?
http://orr.gov.uk/statistics/published-stats/station-usage-estimates
Evening Standard;
● Headline verbs: ‘revealed’, ‘named’. Keywords.
● “New figures” - not bogged down with source detail
● Consider audience: London is the focus
● No quotes. Who could they have interviewed?
Telegraph
● Style: sub-heading before intro
● “Figures from the rail regulator” - no need to name yet
● Moves into reaction by par 4
● Secondary quote: “Told the BBC”
*
https://twitter.com/davidottewell/status/1217046338111787012
*
https://www.telegraph.co.uk/news/2020/12/10/commuters-shunned-train-first-lockdown-rail-figures-show/
https://www.bbc.co.uk/news/uk-england-42196835
https://github.com/BBC-Data-Unit/least-used-station
https://www.thescottishsun.co.uk/news/6351132/norfolk-railway-station-britain-least-used/
https://www.bbc.co.uk/news/uk-england-shropshire-42973820
https://github.com/BBC-Data-Unit/factcheck-stations-demand
https://www.citymetric.com/transport/brief-tour-britain-s-least-used-stations-teesside-4156
Angles come with
pitfalls!
Is that a
lot?
W
ithin
the
m
argin
of error?
A
djusted
for population
etc?
http://tylervigen.com/spurious-correlations
R
isk
of atom
isation?
C
onsider privacy/feedback
Challenge 2: Take an issue
(hypothesis-driven) and see
how many story ideas you can
list using the story categories
Pick one:
Coronavirus
Pollution
Gender pay gap
https://gender-pay-gap.service.gov.uk/
https://gender-pay-gap.service.gov.uk/
https://gender-pay-gap.service.gov.uk/viewing/employer-%2cd-EQDgBs_aYzIwbTF3O-UA!!/report-2017
What did you come up with?
https://pinboard.in/u:paulbradshaw/t:gender+dj+pay
https://www.telegraph.co.uk/gender-pay-gap/
https://www.theguardian.com/world/gender-pay-gap
https://www.theguardian.com/politics/2017/aug/10/gender-pay-gap-widening-at-one-in-four-government-bodies-figures-show
https://www.theguardian.com/news/2018/mar/25/gender-pay-gaps-in-academy-school-chains-among-the-worst-in-uk
https://www.birminghammail.co.uk/news/midlands-news/gender-income-gap-birmingham-its-15940113
https://www.chroniclelive.co.uk/business/business-news/north-east-gender-pay-gap-16085565
https://www.cosmopolitan.com/uk/reports/a27042068/gender-pay-gap-2019-best-worst-companies/
https://www.theguardian.com/society/2018/apr/05/the-uk-companies-reporting-the-biggest-gender-pay-gaps
https://www.bbc.co.uk/news/uk-england-41805053
https://www.theguardian.com/news/ng-interactive/2018/apr/04/gender-pay-gap-when-does-your-company-stop-paying-women-
in-2018
https://www.economist.com/graphic-detail/2018/04/05/britains-gender-seniority-gap
https://www.theguardian.com/news/2018/feb/28/what-you-need-to-know-about-gender-pay-gap-reporting
https://www.theguardian.com/news/video/2018/apr/06/the-truth-about-gender-pay-gap-video-explainer
https://www.bbc.co.uk/news/business-43668187
https://www.bbc.co.uk/news/uk-england-42611365
https://github.com/BBC-Data-Unit/gender-pay-gap
This one’s for free: in Birmingham this company has a 99% mean average pay gap in favour of women, but the median pay
gap favours men. Why might that be? How might the company accounts give you more clues - and a possible story lead?
• Focus on individual data points:
outliers, average, topical
• Filter: categories, sectors
• Format: explainer, interactive, video,
listicle, factcheck
• Reaction, action, response
• Data itself: concerns, campaigns
• Bigger story (merge with other)
• Lead you to interview > story
Filters, formats, reaction, action
and other ingredients
or http://chartchooser.juiceanalytics.com/
● Impact, audience, and practicality
● Bad news (with context); good news
● Power elite (factchecking, accountability)
● Agenda
● Magnitude (scale of problem or data)
Rate using Galtung and Ruge’
news values?
...and Harcup & O’Neill’s?
● Surprise, celebrity, entertainment
● Drama and conflict
● Exclusivity
● Arresting audio-visuals, shareability
● Relevance (to identified audience)
● Follow-up (to events)
• One dataset can generate many
stories. Use the framework to identify
potential angles — then choose!
• Can be data- or issue-driven
• Each angle type raises different
issues — check those are addressed
Key points
Questions!

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