The age of the filter bubble – a small world in a large network

Everyone agrees with me, no-one is arguing against my beliefs, every news article supports my stance – is this what reality looks like? For an increasing number of internet users, it does. Society rarely agrees and varying opinions are the prerequisites for a democratic debate culture. However, since the result of the US Presidential Elections in 2016 we’ve realised that the image that social media gives us isn’t complete and some opinions are even omitted. Whether we like it or not, we live in a filter bubble.

When Donald Trump won the election and became the 45th President of the United States in 2016, many people around the globe were shocked: there was nothing to indicate that this political outsider would be backed by the majority of people. At least that’s how Trump’s opponents saw it. For his supporters on the other hand, it was clear that they were all against Clinton. Both sides had made excellent arguments on the net and expressed their own opinions, but the other side hadn’t heard them. All of them had only read and commented within their filter bubble.

Our society has shifted a large part of everyday life to the internet. For many people, communication and acquiring information happens exclusively online. Facebook’s newsfeed acts like a news magazine, Google as a lexicon, and messengers like WhatsApp or Skype serve as forums for sharing information with friends, colleagues, and family. We now find almost everything we want to know online. Internet providers know that too: Google, Facebook, Netflix, and Instagram know how important their part is in society. They are therefore constantly refining their algorithms when it comes to user-friendliness: they only show us the information that is supposedly relevant to us.

This is nothing new: the popular service providers on the internet collect data about user behaviour on their platforms and promise to adapt the user experience even better to the needs of users – often without them having to do anything. In the past, data collection has been criticised by many experts, but primarily under the (very important) aspect of data protection. The term 'data leech' describes how comprehensive Google, Facebook, etc. collect and analyse users’ personal data: how much time does someone spend online? Where do they live? What are their hobbies?

Of course, all this information is also used by these companies for their own purposes: Google and Facebook earn a large part of their revenue from personalised advertising, for example. But the information should also help to better tailor offers to the respective user. This means not only is the advertising personalised, but also the offers.

As a result, these services only show us the news, information, and opinions that match our user profile. This may seem a positive thing at first: feeds are no longer stuffed with articles that don’t interest you in any way, popular posts are no longer cluttered with comments that you don’t want to read, you don’t have to wade through arguments that don’t lead anywhere, etc. But in the long term, this creates problems that only come to light when you question the filtering mechanisms of social media.

The concept of the filter bubble goes back to the activist Eli Pariser, who in his book, The Filter Bubble: What the Internet is Hiding from You, criticises the extent to which information is personalised on the internet. He notices that different users – depending on their political attitudes, for example – get different results even after using the same search terms. However, the Google bubble is not an isolated case: other services on the web also use algorithms for personalisation. Bubbles like these also occur on Facebook. The problems that result from this, are not only individual in nature, but also have an impact on society as a whole.

Discourse is important in a functioning democracy: exchanging different perspectives is not only important between politicians from different parties, but should take place throughout the whole of society. Only then it is possible to see things from different perspectives and to broaden your own horizons. However, those who live in a filter bubble will rarely find arguments that go against their own views, but are more likely to find a lot of support. Since many internet users do not yet have a sufficiently critical awareness of how to deal with the new media (known as 'media competence'), their own perception within the bubble is projected onto the entire world outside.

Instead of seeing one’s own opinion as just one of many, the filter bubble makes it seem like there is only this one opinion and that no others exist. This explains phenomena such as Trump’s surprising victory. Within the filter bubble of liberal individuals, there were no signs that enough people would share the Republican candidate’s thoughts. Journalists, who are also in a filter bubble like this, act as multipliers and spread this preconceived opinion in other media.

The formation of filter bubbles contradicts two basic ideas that correlate with the spread of the internet as a mass medium: On the one hand, it stands for the networking of the most diverse people across the globe, but anyone living within a homogeneous group will no longer benefit from this advantage. Secondly, the internet has been praised as a virtual place where information is freely accessible and cannot be censored. This enabled the internet to form an antitheses to traditional media, as content is filtered by the respective editorial offices. Now this filtering can also be found on the internet, but instead of an editorial team doing the filtering, it is now an algorithm that selects what users should know.

It is quite easy to presume it’s the fault of large corporations and their algorithms: Facebook, Yahoo!, and Google do not, or only insufficiently, educate their users about how and why they filter certain information, and don’t give them the opportunity to change or disable the filtering. In general, however, all users are jointly responsible for the content they receive. Facebook, for example, shows less news from users whose links we don’t click on. This means that we are already signaling a disinterest in reports that do not agree with our opinion. The algorithm continues to do this and presents only the information that seems to be of interest to us.

Eli Pariser assumes that contradiction is rife in everyone and then compares this with healthy and unhealthy food: we know that we should eat food that is good for us, but we are happy to choose products that will satisfy us at that exact moment. Pariser argues that a mixture of the two should be the solution: information that matches our profile, but also information that challenges us. Algorithms should also be structured in this way.

There’s no party that can take full responsibility for filter bubbles: it seems to be a mix of social and technical phenomena. On the one hand, every person tends to seek confirmation of their opinion. On the other hand, technical developments used in the web are designed to make browsing as pleasant as possible – not to create intellectual challenges. The fact is that one single person can’t possibly see all messages that appear on the internet every day. Therefore, there is basically nothing wrong with a filter based on technical algorithms, but the resulting excess must be examined critically.

Two other terms often appear in connection with the filter bubble, which are 'echo chambers' and 'fake news'. An echo chamber is a room in which you can create a strong echo. In the figurative sense, this refers to a virtual space where opinions only intensify and there are no longer any mitigating influences. Echo chambers like these are created within a filter bubble because a fed-in opinion (e.g. in the form of a Facebook post) is only amplified by the echo of the other members within the bubble and is no longer put into perspective by a different point of view.

Among other things, this explains the success of so-called fake news. The alleged factual reports either depict distorted facts or are even totally made up. Agitators feed these fictional stories into a filter bubble where they can spread these alleged facts without being challenged. This creates a perception of the world that is determined more by opinions than by facts, which leads to conflicts instead of discussions.

There are some voices that criticise the theory of the filter bubble when it comes to diversity of opinions. It is questionable how high the influence of a filter bubble really is and whether the internet or the corresponding algorithms amplify it. According to research by Oxford University, TV was the most popular source of news in 2013 (80% of people got their news from this source), but by 2016, this figure had dropped to 70% and had been overtaken by online sources (72%). The research also showed that 84% of 18-24 year olds get their news online, whereas it’s only 21% of those aged 55+. This age group prefers TV (54%) whereas only 9% of adolescents use TV to keep up-to-date with world events. Since so many people are using the internet for information, the Google bubble could therefore have a significant influence on what information users receive. In addition, journalists also have social media accounts and use Google to research so in this respect, this also influences the media beyond the internet. But there are very contradictory opinions when it comes to the Google bubble: Eli Pariser provides clear evidence of how personalisation influences Google’s search results. However, these observations date back to 2011 and Google continues to make regular changes to its search engine. However, you shouldn’t forget that filter bubbles existed long before the internet: before the development of the world wide web, numerous people in organisations, within circles of friends, and at get-togethers argued their opinions and tried to get others on their side without needing Google or Facebook bubbles. The internet has enabled different viewpoints to be heard and therefore more pluralisation. But to have a free internet in the future, where diverse people with differing points of view and opinions are on the same level, you shouldn’t underestimate the danger of filter bubbles.

If you want to free yourself from your filter bubble, you have several options: the first step should be to question your own surfing behaviour. If you’re looking for conflicting views, you will find them despite the Facebook bubble and Google’s (supposed) personalisation. This is how social media algorithms can be consciously influenced and trained: for example, if you 'like' the pages of several political parties, you should receive a wider range of information from the political spectrum in the future. This way, everyone can create their own diversity. In addition, the network offers tools that at least free the search of personalised results. Every internet user is free to search using search engines other than Google. The German search engine, Unbubble, for example, reveals that no information about its users’ behaviour is collected or evaluated. This means that no personalised search takes place and therefore no filter bubble can form. In addition, there are add-ons for some internet browsers, which help to prevent surfer behaviour from being tracked. What’s good for privacy also helps to prevent filter bubbles. If companies are unable to collect personal data, they can’t personalise results or advertisements. You should also be careful when revealing personal information on social media. If you don’t want to give up Facebook, you can at least be more restrictive when it comes to the data you enter. Assuming that the filter bubble is also expanding into traditional media, it makes sense to use as many different kinds of media and sources as possible in order to obtain information and news. For example, this can be done online by using balanced news aggregators such as Feedly or News360. These enable you to perceive other perspectives and broaden your horizons, despite the menacing filter bubble.