'Twitter has been used in research
significantly more often than any other social media platform'
Large data sets, also called ‘big data’ are routinely collected by private
and public organisations, including law enforcement agencies to monitor human
activity. However, the analysis of such data is still very challenging. Some
methodological issues relating to big data have been identified, one of them
being overemphasis on a single platform.
For example, Twitter has been used in research significantly
more often than its concurrent Facebook. This is due to availability of data,
tools and ease of analysis. Moreover, it is more visible to public, with only
ten per cent of Twitter accounts being private, unlike on Facebook, where only
fifty percent of information posted by its users is publicly visible (Tufekci,
2014). Twitter has much simpler structure – it is
either all private or public.
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| Credit: Arvensystech.com |
Other issues in analysing data include ‘selecting on dependent
variables without requisite precautions’; many ‘hashtag analyses’, the ‘denominator
problem created by vague, unclear or unrepresentative sampling and the
prevalence of studies which overlook the wider social ecology of interaction
and diffusion’ (Tufekci, 2014). Some behaviour can be difficult
to analyse such as clicks, links, and retweets that can have different
meanings, yet they may be combined together by the software. Also, people can
engage in practices that may confuse algorithms, such as subtweets (Tufekci,
2014).
'Humans are far better
than computers at seeing patterns'
It is safe to say that humans are far better than computers
at seeing patterns, integral to the process of creating knowledge, hence the
human presence in analysing the big data is crucial to its success. In law
enforcement, intelligence analysts could be seen as ‘translators of raw
information into usable intelligence’ to help investigators make progress in
criminal investigations, and to support decision makers in creating new
policies based on the researched knowledge. Analysts usually start with identifying
‘what is already known; where data may be found to fill the gaps in knowledge;
how such data might be gained; and the meaning that may be inferred from it’
(James, 2016, p.10).
In
the UK, intelligence analysts are trained using standard analytical techniques
to create four intelligence products. These are strategic assessment, tactical
assessment, subject profile and problem profile. The strategic assessment
provides an overview of current and long-term issues effecting the police force
and sets the strategies to tackle high priority issues. The tactical assessment
identifies shorter-term issues, the subject profile provides better
understanding of person’s interests, while problem profile aims to provide
better understanding of policing problems, for example crime series or hotspots
(Ratcliffe, 2009).
The analysis involves ‘intellectually and technically demanding reporting’ and it has been suggested that performance could be improved by ‘more scientifically and professionally oriented approach’ (Mainas, 2016). To analyse data correctly, analysts need ‘deep contextual and cultural understanding’ of the operation to avoid misinterpretation of data collected, as this could possibly lead to wrong decisions. They are also encouraged to take risks, draw hypothesis and conclusions and ‘provide timely warning of major threats’ (Mainas, 2016).
References:
James, A. (2016). Understanding Police Intelligence Work. Bristol, UK: Policy Press.
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| Credit: fulcrumco.com |
The analysis involves ‘intellectually and technically demanding reporting’ and it has been suggested that performance could be improved by ‘more scientifically and professionally oriented approach’ (Mainas, 2016). To analyse data correctly, analysts need ‘deep contextual and cultural understanding’ of the operation to avoid misinterpretation of data collected, as this could possibly lead to wrong decisions. They are also encouraged to take risks, draw hypothesis and conclusions and ‘provide timely warning of major threats’ (Mainas, 2016).
Intelligence Cycle
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| Credit: Davies, et al. 2013 |
References:
James, A. (2016). Understanding Police Intelligence Work. Bristol, UK: Policy Press.
Mainas, E. (2016). Intelligence Pathologies. The University of Portsmouth.
Ratcliffe,
J.H. (2009). Strategic Thinking in
Criminal Intelligence (2nd edn). Riverwood: The Federation Press.
Tufekci, Z. (2014). Big Questions for Social Media Big Data:
Representativeness, Validity and Other Methodological Pitfalls. Retrieved from
https://arxiv.org/ftp/arxiv/papers/1403/1403.7400.pdf.