According to the Oxford English Dictionary, the Twittersphere is defined as the collective posts made to the ever-large social media platform Twitter.

Such a term connotes the extensive use Twitter sees on a daily basis. The term also implies to me an imaginative yet demonstrable additional layer to the Earth, a digital layer into which everybody is feeding their thoughts and opinions. Whist the collective of life on Earth form biosphere, the collective of data that we produce forms the Twittersphere. The Twittersphere project aims to visualise and tangibilize the Twittersphere into an interactive, meaningful audiovisual experience from which one can gain true insight into what the world is feeling about the topic of the day.

With every local, national, or international event that occurs, those affected by it flood to Twitter to make their opinions known and to join the debate. The individual user is often drowned out by the media sources and figureheads of the debate who, often it seems, harbour bias towards one side of the debate. With such Twitter accounts boasting millions of followers, it is often difficult to view a topic on Twitter without these accounts’ tweets sitting front and centre of the issue. The larger collective opinion on an issue may not in fact align directly with the sampling of individual tweets a user has easy access to.

A currently extremely relevant example of potential media bias influencing a debate is of course that of the ongoing US Presidential election. A quick search for the #MediaBias “hashtag” on Twitter itself proves the lack of trust people have in their media sources this election with the majority of tweets referencing #mediabias also discussing the current election. CNN have especially been put on blast for Tweets so apparently bias they’ve been dubbed “The Clinton News Network“. Again, with such Twitter accounts extremely prevalent in the feeds of many users, it is important to see the collective opinion of the Twittersphere – made up of all users big and small.


Twitter data mining is not an uncommon thing. It is in fact extremely useful for data miners, with examples of applications across a wide range of fields; including solving healthcare issues through patterns in mined twitter data; trend detection for advertising and product analysis purposes; for sociopolitical purposes such as finding people of influence or power within communities; and many more of which can be read in detail here. Many of these applications have very practical purposes, while the goal of the Twittersphere project is more about gaining insight through audiovisual experience rather than data analysis.

There are existing projects that aim to provide the user with insight into the opinions of Twitter users about a specific subject. Two examples are and Both of these projects provide the user with opinions and feelings of Twitter users about the subject, but only on a small scale and without any intelligence of the system itself to determine the sentiment of the tweet – they both simply display the raw tweet to the user. Twittersphere on the other hand aims to remove the text completely from the tweet and display the fundamental sentiment instead through audiovisualisation.

Inspiration for the visual appearance of the Twittersphere is two-fold. Initially, the the idea that the Twittersphere represents an additional “layer” to the Earth in the same way as the atmosphere or magnetosphere influenced us to visualise the Twittersphere in this way – a physical layer of data radiating from the Earth, similar to visualisations of the magnetic field that we’re all familiar with from our school science text books.



Secondly, whilst researching interesting ways to visualise data in this way, I came across the WebGL Globe platform on Chrome Experiments. The WebGL Globe visualises geographical data as “data spikes” emanating from the Earth’s surface with differences in colour and height representative of different data values or types.

This emanation of data from the Earth’s is something that would work well with visualising our tweets. Instead of what is essentially a bar graph in WebGL, the Twittersphere will be visualised with individual tweets radiating from the poster’s geographical location up into space as an orb with the colour and behaviour influenced by the tweet’s sentiment, user’s follower count, and other relevant data.

In addition to visuals, the hope is for sound to play an important role in creating the immersive experience we are creating. By converting the textual data of the tweet to spoken voice digitally, we plan to put the user right into the centre of the Twittersphere “argument” going on around them, with individual voices drowned out by the overall vocal sentiment.

Purpose of the Twittersphere Project

The purpose of the Twittersphere installation is not to form conclusions about a topic, question, or subject. Instead, the purpose is to create an interactive, audiovisual experience through which we aim to create emotional, empathetic reactions from the audience about a topic. We expect that for different subjects, differences in sentiment and opinion might materialise where we may not have originally expected, perhaps on geographical lines or even through time as new information makes its way into the figurative online twittersphere.

We hope that audiences will be able to gain an insight into how opinions on topics and issues differ under different circumstances by focussing on the emotions that people share online, instead of the words they choose to use. In collecting data globally, we hope to break people out of their online echo chamber.

A common concern voiced in both the scholarly and popular press is that the Internet, through its ability to link people to content that reflects their preferences, operates like a giant echo chamber where like-minded people connect with each other and conflicting ideas are avoided (Pariser, 2011; Singer, 2011)

It has become clear through recent events that people are often becoming complacent in their belief that their opinions on a subject are aligned with the majority, only to be proven wrong – often in shock – later on. Before the Brexit vote in June 2016, many including myself felt confident that their choice to remain in the EU was shared by the majority, because everyone they interacted with online shared their views. Similarly with the US presidential election, many internet users felt that their collective distaste for Donald Trump was certain to translate into victory for Hillary Clinton, only to be proved wrong by the so-called “Silent Majority.”

We hope that the Twittersphere Installation will provide a more visual way to break out of the echo chamber that social media users often find themselves in and provide insight into the true global sentiment, and find out whether the silent majority exists or if we just don’t come into contact with them online

Collecting the Invisible – Realtime

As is evidenced from my research, Twitter data mining and analysis is not an uncommon project. In fact, Twitter mining is an extremely contemporary method for creating data visualisations and/or data analysis. Our plan is that the Twittersphere project will stand out as a unique experience that uses Twitter data as the medium through which sentiment and opinion is communicated, and that it is the sentiment and opinion itself that is being audiovisualised.

It is therefore the underlying sentiment that people feel towards a topic or debate that is being collected and analysed live by the Twittersphere project, and the individual and overall global sentiment that is being visualised and analysed by the user. The fact that the data is being collected, analysed, and displayed live as the tweets are being posted means that there is no historical bias being displayed.

The sentiment that is shown once the user hits the figurative “play button” on Twittersphere is the live, realtime sentiment being expressed at that exact moment. Therefore it will always be the Twittersphere’s sentiment towards the issue of the day that is being displayed. This is important, as the headlines and stories about subjects or people can change day-to-day, and it is only the current headlines that gain the most discussion in the Twittersphere.