In order to explore public attitudes towards the use of data from online services (e.g. social media) or digital devices (e.g. mobile phone GPS), we are running a Twitter based campaign (#AnalyzeMyData) in which we reminded people of instances of data usage that have been reported in news stories and asked them to rate if they considered these data uses to be OK. In order to produce momentum of public participation we designed the experiment as a sustained campaign in which a different news item is presented each day over a period of multiple weeks. Each Tweet includes a link to a mini-survey which asks participants to respond, 'yes', 'no' or 'depends'. To further motivate continued participation as the campaign progresses, we provide a running update on our website of the response statistics to the items that were previously Tweeted. The types of data usage included in the campaign range from academic studies of social media use, to data collection for product development, marketing and government studies. Our hope is that this campaign/experiment will 1) help to raise awareness of the various ways in which personal data, acquired through online services of digital devices, is currently being used, and 2) provide a large dataset of case-studies with an associated baseline of public acceptance/rejection that can be used for future research ethics guidelines and review training.

1. Public attitudes to reported instances
of personal data usage
#AnalyzeMyData
A Twitter campaign based survey experiment
Ansgar Koene
Horizon Digital Economy Research,
University of Nottingham

2. CaSMa: Citizen-centric approached to Social Media analysis
•Ethics of internet mediate research
•Citizen perspective on data usage methods
• Conditions for consent
• Attitude to reports of questionable data use
BPS: Ethics Guidelines for Internet-Mediated Research
•Unless consent has been sought, observation of public
behaviour needs to take place only in public situations where
those observed ‘would expect to be observed by
strangers’.
Context

3. AoIR Ethics Working Committee
Public/Private:

People may operate in public spaces but maintain strong
perceptions or expectations of privacy.

The substance of a communication may be public, but the
context might imply restrictions on how that information
ought to be used.

Social, academic, or regulatory delineations of public and
private as a clearly recognizable binary no longer holds
in everyday practice.

4. • The Internet has characteristics that are different from
communication in other channels (Boyd, 2008):

Persistence

Replicability

Invisible audiences

Searchability
People therefore do not have an intuitive sense about the
privacy that they should expect from internet communication
Factors affecting behaviour
and expectations of privacy

5. • Purpose: obtain first-hand data concerning conditions under
which participants would be willing to consent to having their
data used for research purposes
• Targeted at a wide cross-section of the population
• How do conditions for consent change as function of:
•
Participant demographics
•
The type of social network platform
•
The type of organization doing the study
•
The type of question being studied
http://casma.wp.horizon.ac.uk/casma-projects/ccasmd
Questionnaire regarding
conditions for consent

6. N=29, (52%F, 35%M, 13%Not specified), mean age:32,
politics: 75% centre/left-of-centre, 21% prefer not to specify
SM use: 82% daily or more
General consent:
Background and motivation of researcher:
Preliminary results
Academic Corporate Government NGO
Always 58.6 25.5 17.2 27.6
Conditional 41.4 65.5 69 69
Never 0 9 13.8 3.4
Academic Corporate Government NGO
High
importance
44.8 72.4 72.4 79.3

7. Information about analysis method:
Information about how results will be reported:
Am paid for my data:
Preliminary results
Importance Academic Corporate Government NGO
High 34.5 55.2 48.3 51.7
medium 48.3 31 41.4 31
Importance Academic Corporate Government NGO
High 48.3 55.2 58.6 51.7
medium 27.6 24.1 27.6 31
Importance Academic Corporate Government NGO
High/medium 20.6 44.8 24.1 20.7
Low/irrelevant 79.4 55.2 75.9 79.3

8. • Initial participant recruitment:
– www.callforparticipants.com
– Mailing lists: AiR-L; Horizon
– Mention + link in article in
‘the Conversation’
• Responses=29
Problem: How to reach a large
enough broad spectrum audience
3285 article views

9. • Since Twitter is an ‘open broadcast’ style social media
platform it has the potential for anyone to find the tweets.
• More than 1 in 5 people in UK use Twitter (2013 report by eMarketer)
• We are running a parallel project to develop a Public
Outreach Evaluation Tool for Twitter.
Increase survey visibility via
Twitter - #AnalyzeMyData

10. • Build momentum through sustained campaign
– minimum of 1 Tweet/day for at least 1 month
• Increase visibility through use of #tags
– #AnalyzeMyData, for people to find the campaign
– Also include existing related #tags (#privacy, #data, etc)
• Refer to specific instances of questionable data access that
were reported in the media
• Encourage participation via mini-surveys that link to larger
survey
• Maintain blog pages that list items from the campaign +
results
Twitter campaign design

11. • The mini-survey design was tested by posting on the
Zooniverse discussion forum [with admin permission]
Test of mini-surveys

12. • Date 28 January = Data Privacy/Protection Day
• University press release
• Pre-notification to journalists (the Guardian, BBC, Channel4,
Slate, TechCrunch, HuffingtonPost)
– 3 journalists replied to express interest in the topic area,
1 called to ask for further details to pitch to his editors
– None of them picked up the story
• Requested help via AiR-L & Horizon mailing lists for
disseminating the campaign (February 1st
)
• Used re-tweets to add #Privacy, #data, #personaldata,
#PrivacyDay, #digital, #digitalrights
Campaign launch

13. Campaign launch

14. Examples of campaign tweets

15. Campaign results

16. • Total conversions into mini-survey responses: 16
• Total conversions into responses to main survey: 0
• CaSMa Twitter
 +9 followers after announcement on AiR-L
 +22 followers at end of campaign
Survey responses from campaign
2 Consent to monitor fitness
1 Consent to use Social Media profiles for games
5 Consent to have e-mail analysed for ads
3 Consent to experiment for Facebook Newsfeed
3 Consent to for journalists to use Social Media posts
1 Consent to analyse phone GPS
1 Consent for Government to use social networks data for crime
investigations

17. • Twitter is ‘broadcast’ but #tags and Followers are specific.
– Run multiple parallel campaigns each targeting as a
specific segment.
• Promoted tweets reach broad (impressions)
– Low yield (engagement) unless segment specific
• Including known #tags increases impressions but unless
targeted, will be seen as noisy ads.
• Research community in mailing lists is willing to help
promote short-targeted campaigns
• Tweet embedded mini-surveys can work, link-following will
loose participants
• Crafting a clear message + image + link in 140 characters is
difficult.
Conclusions/ lessons learnt

18. Thank you for your attention
Project blog: http://casma.wp.horizon.ac.uk
Twitter: @CaSMaResearch