2014 and the Ministry of Truth | Newspeak: Minitrue

Abigail Leffler says Big Data Brother… one bit at a time

ICT (Internet communications technology) enables gathering of digital data derived from our online interactions and other iterations such as those that come from GPS (Global Positioning System)-equipped devices. This interactivity being ‘a necessary condition for social, cultural and political participation’ (Lievrouw: 2013, p. 15) functions as a catalyst for change, development and humanitarian relief.

Just consider that all the tweets, blogposts and Facebook entries generate big data and so do all the ‘likes’ and endorsements and any other information pointing to user connection networks and to activity levels of individuals on the Net.

To give you an idea of how large big data actually is, every minute of every day we create

  • More than 204 million email messages
  • Over 2 million Google search queries
  • 48 hours of new YouTube videos
  • 684,000 bits of content shared on Facebook
  • More than 100,000 tweets
  • $272,000 spent on e-commerce
  • 3,600 new photos shared on Instagram
  • Nearly 350 new WordPress blogposts

(source: Datamation)

In our previous post Big,BIG, Data Warbles we visited the domain of qualitative analysis of big data. This time around, we are touching on the topic of quantitative analysis of big data. Quantitative analyses permit us to collect sets of data and look at them in numeric values: for example the frequency of rainfall in a certain region, the number of rape incidences in a particular city or the average literacy level in a country. We can then interpret the results and compare them with the same datasets in similar regions or across time to take informed decisions.


Data is big and data is open: WHO (World Health Organisation) Interactive Map (from the Global Health Observatory Data Repository). Click to enlarge.

In addition to the above, big data can be used for non-statistical purposes, for instance to enable more effective aid and humanitarian relief administration. In the eve of environmental stress and disasters such as flooding, earthquakes or war, people tend to scatter, but the GPS-data emitted by their mobile phones as they are on the move can be tracked. Indeed, the ETC (Emergency Telecommunications Cluster) reports that ‘the Haiti earthquake of 2010 turned humanitarian response on its head. The traditional top-down, agency-driven approach of information dissemination was replaced by a groundswell of data from the very people affected by the disaster… emergency response was faced with a new and vital force: social media’ (2013).

There is however an Orwellian downside to big data, and that is called surveillance. There are fears afoot that big data is being used without the explicit consent of the individuals or collectives that generate it. Big data analytics entails no less than privacy breach concerns.

In this respect, we beg to differ from Manuel Castells’s statement when talking about media, ICT and new communication models he expressed that ‘the rise of horizontal networks of communication has created a new landscape of social and political change by the process of disintermediation of the government and corporate controls over communication’ (Castells: 2013). Disintermediation?

Seen from a big data surveillance perspective, the issue with Castell’s statement is that governments and corporations can (and will) retain control over the masses: beware that ‘new technologies [may] enable audiences to exert much greater impact on circulation than ever before, but they also enable [government and] companies to police once-private behaviour that is taking on greater public dimensions’ (Jenkins et al: 2013, p. 54). The posts we blog and the tweets we produce enable governments and organisations to profile and track us. Coming back to the mobile phones GPS-tracking capabilities we mentioned above, researcher at the University of Amsterdam Linnet Taylor confirms our fears: ‘when migrants move, they are increasingly likely to bring a mobile phone with them; this includes undocumented movement’ (Taylor: 2014). This data, which is big and is open, could potentially be ‘made available to border control authorities in order to track migrants who are travelling irregularly’ (op cit). Food for thought…




Castells, M., (2013). The Impact of the Internet on Society: A Global Perspective. Open Mind [online] [Accessed 5 October 2014].

Jenkins, H., Ford, S., Green, J. (2013). Spreadable Media: Creating Value and Meaning in a Networked Culture. New York and London: New York University Press.

Lievrouw, L. (2013). Alternative and Activist New Media. Cambridge and Malden: Polity Press.

Taylor, L. (2014) No Place to Hide? The Ethics and Analytics of Tracking Mobility Using Mobile Phone Data, in Border Criminologies blog [online] Available at: http://bordercriminologies.law.ox.ac.uk/tag/surveillance/ [Accessed 17 October 2014].

Unknown (2014). Global Health Observatory Data Repository, in the World Health Organisation website [online] Available at: http://gamapserver.who.int/gho/interactive_charts/cholera/atlas.html?indicator=i1 [Accessed 17 October 2014].

Unknown (2014). Social Media in Humanitarian Response, in ICT Humanitarian Emergency Platform website [online] Available at: http://ictemergency.wfp.org/sv/web/ictepr/wavelength18/social-media-in-humanitarian-response [Accessed 17 October 2014].

Vance, J. (2013). Big Data Analytics Overview, in Datamation website [online]. Available at: http://www.datamation.com/applications/big-data-analytics-overview.html [Accessed 14 October 2014].



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  1. Maureen Van Dreumel

    Hej Abigail! I really appreciate the level of detail provided in your blog post: it’s incredibly informative and well substantiated. This is another great trait of inspiring blog posts: useful detail…
    It is very much of a ‘Catch 22’ situation, isn’t it? that the networks are largely developed, owned and controlled by big companies and government, so they almost ‘own’ us and the data we generate. But the potential uses for that data are very seductive in their potential utility, as per your WHO map and example of aid logistics. I wonder if it will always be a ‘mutual use’ relationship? It’s the balance that’s so hard to get right…ethics vs effectiveness…

    • Abigail Leffler

      Thanks, Maureen! I agree with you – it is a ‘Catch 22’ situation indeed.

      The current discussion around big (and open) data is not only who owns it and what it is used for, but also in which manner (which method) statistics and reports are produced. The danger is that data can be manipulated in such a way that whilst not lying it is not telling the whole truth either. It is all a matter of angle.

      Audiences do not seem to be critical enough to question the validity of sources, either. And, ultimately, who has authority to decide what is true and valid anyway?

      It is not that this situation is ‘new’ to humanity, but the Web 2.0 phenomenon with its big/open data companion seem to have augmented both its positive and negative potentials.

      Thank you again for taking the time for reading our posts and commenting on them!

      Much obliged


  2. Thanks Abigail for this well placed risk assessment and concern.

    I believe that the risk is as great as the potential, especially given the global reach that smart phones have experienced in the recent years, they are everywhere – even common in the least developed countries. We know all data is saved and we know that data is shared by companies, such as Facebook and Google, so what is stopping corporations or authoritative figures to exploit this data?

    Another concern I had while reading this post is that data is also just cold, raw information, which needs careful interpreting and analysis and even then, it often lacks context or the human factor. In our past studies, criticism was placed towards the “top-down” development that sometimes occurs in large organisations, where decisions are made on a global level, without consideration of local needs and customs. The “eye on the ground” has always been an absolutely necessary factor. Blind faith in big data can backfire, if taken for truth above all else. An example for this are inaccuracies of the “Google Flu Trend”.


    • Abigail Leffler

      So true, Johannes. Sadly, we are left at the mercy of the ‘data interpreter’ and the fact of how much (or how little) they may be able to relate to the bigger picture.

      For my individual assignment I am studying the International Crisis Group; they have people ‘on the ground’ so they claim their reports are more ‘accurate’ and ‘realistic’. Like ‘bias’ does not exist if you are on the ground…