Keynote from the MIPAA Masterclass, Friday 23rd January 2015, LCC, University of the Arts London

1. Convergence, Computation &
Continuity: Social, Ethical and
Practical Challenges for PR
Simon Collister

2. Today
1. Convergence > What’s happened
2. Computation > What’s happening
3. [Diversion] > Impact on PR
4. Continuity > Where next?

3. C1: Convergence

4. Convergence: What do we mean?

5. “Convergence Culture”
“The flow of media across multiple platforms, the
cooperation between multiple media industries,
and the migratory behavior of audiences who will
go almost anywhere in search of the kinds of
[entertainment] experience they want.”
(Jenkins, 2006: 1)

6. That Was Then…

7. … This Is Now.
“Companies are battling for attention – the notion of ‘continuous partial
attention’ highlights the fact that individuals now divide their attention
among different devices, daily activities and real life conversations […]
How, as a company, do you grab consumers’ attention in this
landscape, capturing them on them on the go, without interrupting their
daily routines? This will be an even bigger challenge with the arrival of
smartwatches and the rise of ‘glance media’ associated with it.”
Sandrine Plassaraud, Managing Director, France, We Are Social

8. Media Convergence: 2015
• Mobile becomes mind-set and behaviour, not just a platform
• It is “the primary means for consumer engagement. As these
new norms take shape in the hands (and on the wrists) of
consumers, brands should be prepared to find new ways to
offer value and engage in these diverse, always on contexts”
Leila Thabet, Managing Director, New York, We Are Social

9. Internet of Things?

11. C2: Computation

12. Rise of the Machines?
• Corollary of ubiquitous media
digitization is increased
importance of computation
• Software increasingly enabling
and shaping communication

13. Sorry, what?
Manovich (1999; 2012) argues that default ‘logic’ of communication in
the digital age is the ‘data base’ and ‘data stream’

14. Ah. OK.
Data Streams…
“do not tell stories; they don't have beginning or end; in
fact, they don't have any development, thematically,
formally or otherwise which would organize their
elements into a sequence”
(Manovich, 1999: 80)

15. No, sorry. What?
• The distribution, visibility and sense-making logic applied
to data is performed increasingly by algorithms
• That is, by sets of rules that directly govern the
behaviour and function of data (Lash, 2007: 70).

16. Like this…

17. So what does this mean for strategic
communications and public relations?

18. Computational Communication?
• Communication activity requiring the
deployment of algorithms to collect and
analyze data collected from converged
devices and process this information for use
in developing, implementing and evaluating
communication strategies?

19. Computational
Communication:
Some Examples

20. Data Analytics
• Algorithms play central role
in sense-making (Heide,
2009; Walker, 2009)
• Identifying, categorising and
segmenting audiences key
role of public relations

21. Google PageRank

22. Non-Representational Strategies

23. Facebook Algorithms
• Edgerank controls
the News Feed
• Auto-moderation
manages your
Page content

24. [Diversion] Impact on PR

25. PR’s Social Role
• PR produces “social and cultural meanings”
(Edwards & Hodges, 2011: 4)
• PR socially constructs, challenges and shapes
society’s values (Ihlen et al., 2009)

26. PR’s Social Power

27. Algorithmic Power?
Through digitized media, algorithms are actively:
• “producing and certifying knowledge” (Gillespie, 2014:
168)
• “enabling and assigning meaningfulness” (Langlois,
2010: 100)

28. Who/What Shapes Society?

29. Ethical Impact
• Interesting from an ethical perspective too
• PR becomes guided by a ‘quasi-subjectivity’ -
decisions for and effects of communicating are
no longer determined by human agency

30. Algorithmic Responsibility?
• PRSA requires practitioners to “protect
and advance the free flow of accurate and
truthful information” and “foster informed
decision making through open
communication”

31. What’s inside the box?

32. Algorithmic Transparency

33. C3: Continuity

35. Paid Media
• Part of algorithms’
rise is monetization
• Can pay to by-pass
their effects
• Requires investment
in new roles, skills
and paid budgets

36. Improving PR’s potential
• Berger & Meng (2014) identify “dealing with the speed and volume
of information flow” as key challenge for PR practitioners globally
• More data means more insight – providing investment in algorithms
(or tools using them)
• Means better targeted and more effective PR

37. Rise of the Humans?
• Work with algorithms:
create clear, interesting
content which sounds and
looks like something a
human will want to
read/watch/hear

38. Questions?
s.collister@lcc.arts.ac.uk
@simoncollister
www.simoncollister.com

39. References
• Berger, B. K., & Meng, J. (Eds.) (2014). Making Sense of Public Relations
Leaders – The Sense Makers. A Global Study of Leadership in Public
Relations and Communication Management. New York, NY: Routledge.
• Edwards L and Hodges CEM. (2011) Public Relations, Society & Culture:
Theoretical and Empirical Explorations. Abingdon: Routledge.
• Hamilton, J. T. and Turner, F. (2009) ‘Accountability Through Algorithm:
Developing the Field of Computational Journalism’ report from Developing
the Field of Computational Journalism. Center For Advanced Study in the
Behavioral Sciences Summer Workshop, July 27-31, 2009.
• Heide M. (2009) On Berger: A Social Constructionist Perspective on Public
Relations and Crisis Communication. In: Ihlen Ø, Ruler Bv and Fredriksson
M (eds) Public Relations and Social Theory: Key Figures and Concepts.
New York and London: Routledge.

40. References
• Ihlen Ø, Ruler Bv and Fredriksson M. (2009) Public Relations and Social
Theory: Key Figures and Concepts. New York and London: Routledge.
• Jenkins, H. (2006) Convergence Culture. New York, NY: NYU Press.
• Lash S. (2007) Power after Hegemony: Cultural Studies in Mutation.
Theory, Culture & Society 24: 55-78.
• Manovich L. (1999) Database as Symbolic Form. Convergence: The
International Journal of Research Into New Media Technologies 5: 80-99.
• Manovich L. (2012) Data Stream, Database, Timeline: The Forms of Social
Media Available at: http://lab.softwarestudies.com/2012/10/data-stream-
database-timeline-new.html (accessed 24th March, 2014).
• Walker G. (2009) Sense-Making Methodology: A Theory of Method For
Public Relations. In: Botan CH and Hazleton V (eds) Public Relations
Theory II. Mahwah, NJ: Taylor & Francis.
• Grant, R. (2015) The Evolution of Social in 2015. We Are Social blog.
[Online] Available at: http://wearesocial.net/blog/2015/01/evolution-social-
2015

41. Convergence, Computation &
Continuity: Social, Ethical and
Practical Challenges for PR
Simon Collister
London College of Communication:
UAL