We all know somebody who laments the rise of social media, often purporting that it erodes social cohesion. There is, however, a sizeable body of evidence to suggest that this is not the case, as long as we’re wise about what we see, where it’s coming from and where we fit in.
In their book “Connected,” Christakis and Fowler argue that the “hyperconnected” world made by possible by technology is, in fact, helping us to realize our natural instinct to connect with other humans. They note a 2011 national survey showing that 80% of internet users participate in a group or voluntary association compared to only 56% of non-users. While it is difficult to say that being online causes better social cohesion without a more rigorous study design, a growing body of similar evidence at least provides the basis of a strong association.
Supporting the above is the observation that, in many cases, our behavior online is closely related to what we do offline. In Netville, a Toronto suburb, residents who were better connected with other residents online came together more frequently as a community and successfully protested defects in the construction of their homes. The relationship between online and offline behavior can even be seen in unforeseen areas. In 2005, an infectious outbreak in the online game World of Warcraft went much further than the developers had planned because of the way players interacted with each other. The episode required a complete reboot of the game’s servers and provided lessons for real world outbreaks as reported in Lancet Infectious Diseases. In reverse, it seems our online behavior also influences our real-world interactions. A research group at my alma mater – University College London – showed that a virtual reality experience in the form of an avatar can help to reduce self-criticism and increase self-compassion and feelings of contentment.
With this interdependence, it would seem all the more important to analyze what we are seeing online and, crucially, what – or who – is influencing this. Cue the entry of the Filter Bubble.
Many of us are familiar with the idea that our Facebook feeds are tailored to what Facebook’s algorithm thinks we want to see, even if we aren’t comfortable with the idea. This process extends into our Google searches and beyond, and has come to be known as The Filter Bubble. In his TED talk, Eli Pariser warns us that its unrestrained and uninvited use will lead to a less balanced diet of information, and ultimately a degradation of democracy by failing to provide us with alternative points of view.
Accepting there’s some gravity to the idea of a Filter Bubble, it’s important to consider how profound its effects may be. As humans, we are incredibly vulnerable to being swayed by external opinion. In the 1950s, the Asch experiment demonstrated that a majority group can influence us to knowingly choose the wrong answer to a simple problem. This effect is seen in all industries, and is at the heart of why organizational change is so difficult. Indeed, awareness of how we might be swayed is a cornerstone of many leadership development programs, including those I’ve benefitted from.
There are, of course, those who dispute the significance of the Filter Bubble. Jonathan Cray provides a thorough critique; one study of 250 million users found that most of what we share online is likely to come from our weaker ties and acquaintances, who are less likely to share our political or other beliefs. The size of such a study is worth mentioning in itself and minimizes the effect of random error on the results.
Beyond the Bubble, whose effects are largely due to algorithmic code, the control of the infrastructure supporting the internet has the potential to affect what we experience online without our knowledge or consent. The principle of Network Neutrality implies that Internet Service Providers (eg Comcast and Verizon in the US / BT and Virgin Media in the UK) should treat all internet traffic equally, but not everybody agrees. Proponents argue that Network Neutrality ensures equal access for new innovation, but opponents argue that the principle – and supporting legislature – disincentivize the Providers from investing in new, high speed infrastructure.
Regardless of any potential dangers of the Filter Bubble or a lack of Network Neutrality, online social networks are set to play an increasingly important part in our lives. Social Network Analysis (SNA), as described by Rheingold, gives us some tools to increase our awareness of how we fit in. We can assess our links to other individuals not only by the strength of our ties, but also how central we are within a network; having high “centrality” implies that somebody is good at bridging the gap between differing parts of a network. This is, within many industries, seen to convey a particular advantage.
The flipside of centrality brings us back to look at Infectious Disease, though this time there are a great many examples in the real world to demonstrate this. Focusing on a study from a 2015 outbreak in South Korea of the Middle East Respiratory Syndrome Coronavirus (MERS-CoV), there were 186 patients affected in a 3 month period. By investigating the epidemiology of the outbreak, the authors showed that one man, named “Patient 14” was linked to 82 other cases of MERS-CoV, or nearly 45% of the total cases seen in the outbreak, earning him the title of “superspreader.” His centrality to other patients in location and time allowed him to spread the disease to many more people than would typically be expected.
Social networks have great potential to further enhance social cohesion, through the interplay between our online and offline behaviors. But to navigate the digital world, it would be wise to have a keen awareness of the ways in which information is filtered before it reaches us, and the centrality of our position within our social networks.