08
Nov 16

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.

REFERENCES

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.


08
Nov 16

Digital Humanitarians

Shahin Madjidian

The previous posts have been somewhat negative of what big data can accomplish and the effects it may have on privacy and democracy. But are there no positive sides to it? It turns out there is!

Patrick Meier is the author of the book Digital Humanitarians: How Big Data Is Changing the Face of Humanitarian Response. In the book, he lays out a large number of examples of how he and his colleagues and friends have developed and led digital humanitarian relief and aid efforts during catastrophes with the help of big data.

It all started with the earthquake that hit Haiti in 2010. Meier’s interest in this event was sparked by the fact that his partner currently worked in the country, so he had a very personal reason for starting the digital relief effort. I think this may have been one of the main reasons why Meier continued to work with and develop digital humanitarian efforts later on – his emotional attachment to what could have been, had his partner not made it out of there.

What started as a small-time operation in a campus dorm quickly grew to something that even attracted national and international agencies. Meier himself was surprised, not only by what they were able to accomplish, but also the fact that what they did actually was possible for a beginners group like them, without any previous knowledge or expertise in the humanitarian field.

As the book progresses, Meier’s work and tools develop as he and his colleagues face scenarios with unique challenges. It is about automation in order to handle to huge amount of data that flowed in, it is about streamlining the organization, it is about educating the digital volunteers, and much more.

But the one thing that keeps returning, regardless if it is about Meier’s own efforts or the efforts of others, which the book also presents, is the importance of involving people with local knowledge. “Locals” can identify buildings, landmarks, streets and therefore become a great asset during the analysis part of the digital humanitarian effort. The “locals” also speak the language where a catastrophe has taken place, which for the most part is not English. Without this possibility to translate aid requests, Meier and his team would never be able to figure out which need was needed where.

By constantly returning to this aspect, Meier confirms the notion that big data requires local knowledge in order to properly be analyzed and used.

Another thing that constantly returned throughout the book was how smooth it was for Meier to solve the challenges that kept popping up. He always knew the right person at the right universities or agencies, which he had met during this or that conference, who knew exactly how to deal with an unexpected issue that was unique to a certain humanitarian crisis. After a few chapters it almost became absurd. It is absolutely amazing that Meier has this kind of network, but in all honesty, how many have so many great contacts? Obviously, this brings us back to the question of who big data is useful for, and who is able to handle big data.

Lastly, Meier makes sure to note that all his projects and programs are freely available. This also sounds good, but is he the future norm of big data, or rather the exception? Going back to my first blog post about ownership, I dare say Meier seems to be the grand exception, at least if status quo is kept. However, he does offer a refreshing alternative which I would hope more actors within the big data field will emulate sooner rather than later.

All in all, this book gave me a different perspective to big data and how it can be used to do good things and not only for commercial purposes. I did feel somewhat more positive writing this post compared to the previous ones. But exactly because the perspective was so different, my negative opinion of big data presented in the first two blog posts wasn’t changed much by the book. Meier doesn’t discuss privacy issue much and when he does, he believes that the ends justify the means. A critical view of ownership of big data is non-existent and there is neither a deep discussion on social media users related to power and income questions.

REFERENCES

Meier, P. 2015: Digital Humanitarians: How BIG DATA Is Changing the Face of Humanitarian Response. Boca Raton, FL: CRC Press.


07
Sep 16

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