To what extent can social media impact behaviour change?
I came across a Bloomberg article this morning that described how China fakes 488 million social media posts a year. As the article went on to describe numbers, timings and content, it ended with an interesting paragraph:
““The main threat perceived by the Chinese regime in the modern era is not military attacks from foreign enemies but rather uprisings from their own people,” they said. Revealing a paternalistic approach, the guiding policy of China’s Fifty Cent Party appears to be that distraction is better than conflict. “Letting an argument die, or changing the subject, usually works much better than picking an argument and getting someone’s back up (as new parents recognize fast),” they wrote.”
Described as distraction but if we dig deeper, isn’t it simply behavioural change?
Let’s take the usual textbook example of the Arab Spring which began in December 2010 in Tunisia. It was demonstrated that the protests took place in states which had a significant level of Internet usage as well as the states with low usage like Yemen yet the use of social media platform saw a significant growth during the protests. From polls to pages on Facebook to blogs, people aimed to raise awareness locally and internationally and cast the light on the situation.
In this case, social media was not everything but heavily contributed in the sense that it helped to break the psychological barrier of fear and contributed to “spread information.”
The Bloomberg article on China spreading 488 million social media posts to spread content about local events (i.e: posts which claimed economical development post July 2013 riots in Xinjiang) or to criticise the west is an example of misinformation, with the goal of keep its people in line.
Beyond the spread of content, a discussion also needs to be had about how it appears on your computer screen. Or more importantly, on your newsfeed. With multiple algorithms, content is carefully selected to appear at a certain time. For example, if you’ve visited an online shop and you’ve looked at a few items, they’ll retarget you with the items you’ve looked at. And products related to those products.
If you’ve visited Slate’s website, or the Guardian’s or the Independent that’s an op-ed piece about the future of the Middle East, these publishers will then carefully select further content either about the Middle East, or written by the same journalist, or with the same tone of voice, or any number of other permutations and combinations.
The same is true for your search history. For the ads you click. The websites you spend the most time on.
The retargeting falls under behavioural targeting. As described by Blue Fountain Media:
“Behavioral targeting is a technique used by online publishers and advertisers to increase the effectiveness of their campaigns through information collected on an individual’s Web-browsing behavior (…) The technique helps deliver online advertisements to the users who will be the most interested in them. Behavioral data can also be combined with other user information such as purchase history to create a more complete user profile.”
From a wider perspective, how is this content interpreted by its readers?
It is difficult to think that we can remain stoic to all the aggressive constant online advertising whether it’s targeted ads or those emails that fill up our inbox. Can we really claim that this doesn’t shape us? This constant barrage of information seeding thoughts and ideas that we consume for multiple hours in a day doesn’t in some way alter who we are? Or what we think?
Having a profile with our behavioural data online which knows where we go to look for what and our online habits only makes it harder.
As estimated by Eric Schmidt, humankind now captures the same amount of data in any two days than in all of history prior to 2003. Isn’t that scary?
What data is being captured exactly?
According to Colin Strong in his book Humanising Big Data, we now have database of how people are feeling. With over one billion people active on Facebook, we have status updates, photos, life events… Through social listening, companies can scrape the web and gather sentiments around their products or issues. The datafication of interactions and relationships is also possible as we are now able to go beyond the ways in which people related but also have an idea of whom they relate. We can now explore relationships on a global scale. Also, what was traditionally seen as offline activity can now be datafied.
Finance, healthcare and e-commerce just to name a few, are examples of data-intensive industries which have a significant amount of information on individual behaviours. Beyond this, we can think of in-store cameras, facile recognition software and more of these innovations that are growing more sophisticated. We actually say Big Data instead of just simply data because of its volume, its velocity (real-time), variety, flexibility and exhaustiveness (entire populations).
With this in mind, can we think of any challenges that can slow Big Data down? Big data hubris does exist and Google Flu was the perfect example. Google decided to track behaviours of people with the flu going online and searching for treatment. The goal was to predict flu outbreaks faster than traditional health authorities. The issue? The human factor.
Thinking you have the flu, does not mean you actually have the flu. Most people don’t actually know what the flu is and simply reply on Google searches yet “Too much information kills information and leads to misinformation”.
The human factor does play a role in there being a challenge for Big Data to fully predict our future needs and determine our behaviour. Things like the cognitive inertia play a role in which beliefs endure once they are formed, makes it difficult for humans to be wired for change. The question of actually interpreting data requires “sense-making” which means making meaning from experiential and situational awareness, something computers and some people can’t do. Lastly, does more data mean better decisions? With more and more data coming in, more time is actually required to interpret it.
The point to this? Yes, our digital exhaust will contribute to giving more information about us allowing our user profile with our habits and interest. Big Data will be able to give businesses an estimation of our short-term needs but yet, there remains a challenge in predicting our future needs as well as fully determine our behaviour simply because of the human factor. There is only a limit in which we can quantify feelings, emotions or sentiments.
Going further:
