trainspotting - content analytics and online research

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Stop looking at carriages start looking at trains John Griffiths March 8 th 2011 Planning Above and Beyond

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presented on newMR webinar in Feb 2011 - this argues that content analytics needs to frame by theme (the train) before analysing individual carriages (keywords) - related to the cloud of knowing open source project - this brings together discourse analysis and online data

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Page 1: Trainspotting - content analytics and online research

Stop looking at carriages start looking at trains

John GriffithsMarch 8th 2011

Planning Above and Beyond

Page 2: Trainspotting - content analytics and online research

Cloud of Knowing

Face to face meetingsNext one due in April

Sharing papers

Open source project

http://www.webjam.com/cloud_of_knowing

Remit to consider how online content can beincorporated robustly into market research

Page 3: Trainspotting - content analytics and online research

The tool nearest to hand is NOT necessarily the best one.. Just the closest

Stochastic (counting) tools are easy to write

It doesn’t mean they tell you very much

Page 4: Trainspotting - content analytics and online research

Totem talk from Rosie Campbell

Start with shared meanings Cultural discourses Family stories Telltale words used

Only look at the componentwords when you understandthe shared context

Several totems in each market – demarcate each oneTHEN identify component words

Source: Inside language - how to spot totem polesRosie Campbell MRS conference 2010

Page 5: Trainspotting - content analytics and online research

You don’t understand a train by counting carriages

Page 6: Trainspotting - content analytics and online research

The meanings come from abovenot below

Obese = lazy and complacent

Who I am – tied into my weight

Uses ‘obesity’ to repel her from it

Can’t bring herself to use the ‘obesity’ word

‘people’

usvs

Page 7: Trainspotting - content analytics and online research

Branding trains

Page 8: Trainspotting - content analytics and online research

Attaching brands to trains..

Can be artificial – imposed Better to discover which train the brand

fits with And find the right time to make the brand

connection – in the right part of the train Fill the train – don’t try to own it

Page 9: Trainspotting - content analytics and online research

Tying this down..

Using qualitative analysis or reanalysis of existing studies to identify different trains, the mix of carriages – analysis by hand

THEN use analytic engines to track the train – analysis using automated processes

Page 10: Trainspotting - content analytics and online research

Pick the right platform

Sampling

Page 11: Trainspotting - content analytics and online research

The curator curve

Posts regularly on a topicOften refers to own postings

Posts one off commentsNo evidence of deeper interest

NB not the sameas authority orinfluence

Page 12: Trainspotting - content analytics and online research

The audience curve

Online hit – viewed by thousands or hundreds of thousands

Rarely if ever read by anyone!!

Page 13: Trainspotting - content analytics and online research

The context curve

Detached from context

Actively involved/immersed in context

Reflective but away from context

Page 14: Trainspotting - content analytics and online research

Insomnia: which gives the best picture?

Detailed diary contentby insomnia sufferers

Regularly accessed andrated content

When and where thecontent was createdeg video andphoto content

Page 15: Trainspotting - content analytics and online research

Work TOP down – sort the trains before the carriages

Sample – grade the data rather than increase the size of the dataset – to bring clarity – reduce noise increase signal

Don’t use a tool just because its there or because its free..

Page 16: Trainspotting - content analytics and online research

That’s all folks!