Big Data and Anecdotal Evidence

Shahin Madjidian

This last blog post of mine will discuss the paradox between the growth of both scientific big data and emotional anecdotes. There seems to be a tug of war between on the one hand big data and on the other hand anecdotes and emotions (Aday, Farrell & Lynch 2010:5). How do they compare and interact?

On the one hand we have big data, science, facts, and numbers, as has previously been described and analyzed. On the other hand we have anecdotal evidence, conclusions many times based on emotions. Both grow in impact and spread as social media and internet connectivity grows. Is this a paradox? How can it be explained?

Explaining big data is fairly obvious. The more we use social media and various sites online, the more tracks we leave behind us, ready to be collected, compiled, analyzed and used. Big data today is usually defined as a compilation of fragmented data from many users, but it is hardly revolutionary or thought-provoking to suggest that soon all kinds of data stemming from one individual will be collected and analyzed, making the individual one big emitter of big data itself.

But in this day and age of facts, numbers, and data in each and every corner, how come there are so many people believing in anecdotes, the experiences of others, and the rule of emotions? I believe that this can be traced back to the notion of ‘slacktivists’ and the power of numbers, combined with the still new feeling that “hey, there are others like me out there!”. As Barberá et al. state it, “by expanding the audience of messages sent by the committed minority, the periphery can amplify the core voices and actions, and thus provide a way for larger numbers of online citizens to be exposed to news and information about the protest” (Barberá et al. 2015:11).

Then US Secretary of State Hillary Clinton said about new media technologies that they open plenty of doors, but that there are dark ways it can be used too (Aday, Farrell & Lynch 2010:5). Even though she probably didn’t refer to the anecdotes I discuss here, her point that new media and social media isn’t something inherently good is still valid. For me, one clear danger is how posts, rumours, anecdotes, and sometimes even pure lies, can go viral and become the truth of the day thanks to how easy information can be shared and spread, especially within sub-groups.

One such consequence becomes related to social capital, more especially to the potential growth of bonding social capital. Bonding social capital is when the level of trust between members of a sub-group is high, but the level of trust to outsiders is substantially lower, as opposed to bridging social capital, which refers to high levels of trust between members of two or more sub-groups. Does access to new media bond individual groups tighter together, creating polarization, or does it bridge groups together, creating more understanding and fostering “cross-community communication” (Aday, Farrell & Lynch 2010:10)?

As we humans are pack animals, we tend to be attracted to likeminded people so that our ideas, traditions and prejudices can be confirmed, boosting our self-confidence of being right. I don’t want to qualify this challenge for societies as the most important challenge to deal with, but I do believe that it is of vital importance to continuously work towards spaces where interaction between sub-groups is both possible and required. It is only in the meeting and conversation lies and prejudices can be shattered.

So, “social media may reduce the transaction costs for organizing collective action, by facilitating communication and coordination across both physical and social distance” (Aday, Farrell & Lynch 2010:10f), which in turn may lead to an increase in bonding social capital and subsequent polarization in society, as humans gravitate towards those who share their beliefs and have the same experiences, resulting in an increase in anecdotal evidence based on emotions.


Aday, S., Farrell, H., Lynch, M. et al. 2010: Blogs and Bullets: New Media in Contentious Politics, Washington, DC: United States Institute of Peace.

Barberá P., Wang N., Bonneau R., Jost J.T., Nagler J., Tucker J., et al. 2015: The Critical Periphery in the Growth of Social Protests. PLoS ONE 10(11): e0143611.

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1 comment

  1. Filters, Algorithms and Sovereignty

    Will digital life be enough to explain our life as a whole or it will just be a slightly better piece of us apportioned from what is our existence as a total? Can big data give a satisfactory image of an individual if consisting only of our digital “imprints”?

    Reading a post or passing our day chatting in social media creates emotions which sometimes are hidden. Such emotions are hidden into the “why” we post, why we pass so many hours being out there in the web which cannot necessarily be explained in the amounts of data accumulated. Probably sometimes are our hidden emotions in play during all this process and that’s something hard to describe in stats, unless emotions’ analysis will grow much faster in the near future.

    This (hidden emotions) could probably be a reason why polls failed recently to discover voting intentions in many parts of the world. Because such emotions couldn’t be always described in a text or even a speech.

    Another question that comes in my mind when reading this post is who will maintain “in life”such vast amounts of data? Energy, space, infrastructures and personnel needed. So probably poorer countries will need help either from bigger countries or organizations (public or private) to have an idea about their citizens, their social problems and what’s urgently asked to be fixed. Data sovereignty will be the next big thing… Sean Martin Mc Donald writes about problems arising while discussing about Ebola in Liberia (Mc Donald, 2016, p.15).

    Sending a post about a social mobilization is not necessarily without filters. A filter can be how long it will stay visible. Algorithms that prefer one post from another (deciding the visibility order) and thus give to some of the power to expand more. Education on how algorithms are built could be the next positive thing for democratic societies.

    Α part of the post I really liked was how “rumors and… lies can go viral”. As the globe reacts more and more rapidly and even professional journalists don’t have time to ask why, we should question ourselves if one day can be enough to turn the tables over a critical decision in such a case.

    The more “closed” a group is and the more our existence is limited only there (to this group), the higher are the possibilities not to question critically what is accepted as a group value or credo (Windisch 1990 in Campion & Van De Winkel, 2016, p.44).

    More global views and exchanges will not necessarily lead to agreements, but will help to confront polarization and facilitate opposites to know each other. Like in the rest of our lives, closing up ourselves only in sub-groups can cut us out from parts of reality…Development should be through and over global exchanges.

    Campion, Baptiste and Van De Winkel, Aurore (2016), La logique des complotistes, Sciences Humaines, Mensuel No 287, Décembre 2016.

    Mc Donald, Sean Martin (2016) Ebola: A Big Data Disaster: Privacy, Property and the Law of Disaster Experimentation, CIS Papers 2016.01, March 2016, Bengaluru and Delhi: The Centre for Internet and Society. Retrieved: December 1, 2016 from