Category Archives: Web Science Institute

Real-time Twitter Visualisations for the US 2016 Presidential Elections

Twitter Visualisation at RPI For the 2016 US Presidential election, researchers at the University of Southampton with support from the EPSRC funded project SOCIAM,  built a real-time data visualization that combined traditional polling data with social media posts. The application was built and designed for the Rensselaer Polytechnic Institute EMPAC Campfire, a novel multi-user, collaborative, immersive, computing interface that consist of a desk height panoramic screen and floor projection that users gather around and look into. The application is also a part of the Web Macroscope (a visualization platform developed at the University of Southampton) and uses data from the Southampton Web Observatory.

Data collection for the polling data was taking from the Huffington Post Pollster API, which collects all the popular polls and their results. The social media data was collected on Twitter, using both their Streaming and Search API. The Streaming API was used to create a stream of data that included 1% of all tweets that had any of the popular and official hashtags and words used by each campaign to show support for their candidate. This hashtag list included tags like ‘TeamTrump’, ‘maga’, ‘TeamTrump’, and ’draintheswamp’ in support for Donald Trump, and ‘LoveTrumpsHate’, ‘ImWithHer’, ‘StrongerTogether’, and ‘WhyIWantHillary’ in support for Hillary Clinton. Any tweets that mixed hashtags and words from both candidates were removed as this was normally done in a way to not show support for a candidate, but to react to supporters on the other side.Campfire visualisation of US election Twitter activity
Results from the visualizations showed different levels of support on Twitter for each candidates over time. In the days leading to the election on November 8th, tweets in support for Trump were 1.5 times greater than those in support for Clinton. Interestingly, on the day of the election, this ratio switched and levelled off. Around the 2pm EST on November 8th, tweets in support for Clinton were almost equal to the number of tweets supporting Trump. Later in the night of the election, the ratio of support changed again, with tweets in support of Trump being 1.14 times larger than those in support for Clinton.
Another interesting result from the data, was the how many tweets that had geographic information tagged to them were overwhelmingly in support for Clinton throughout the day leading and on the election. Most tweets streamed through the visualization had no GPS lat/long data embedded in them (these tweets often come from mobile phones using the Twitter App, with the optional GSP location data option enabled). As a whole, these geographic tweets are a small minority of the data collected from the Twitter Stream (about 1%). Interestingly, these geographic tweets supported Clinton 15 times more than Trump. Why this is the case is hard to say. It looks like Clinton supporters use mobile apps with location data more than Trump supporters.
Two other studies – one from researchers at USC, and another from Oxford University, the University of Washington and Corvinus University of Budapest,both showed that AI controlled bots were spreading pro-Trump content in overwhelming numbers. This created the illusion of more support for Trump on Twitter than make naturally been. Our results of geotagged tweets in support for Clinton, despite overall support from Trump on Twitter might be due to this issue of bots.
Authored by Dominic DiFranzo, 18 November 2016.

Web Science: The Age of the Social Machine

Anni Rowland-Campbell speaking at the University of Southampton/Digichamps ©2016
Anni Rowland-Campbell speaking at the University of Southampton/Digichamps ©2016/cc by-nc

At the Web Science Institute seminar held earlier this week WST board advisor, Anni Rowland-Campbell spoke on the socio-technical changes that are happening in the world as a result of the Social Machine, which began with the World Wide Web. The talk focused on Tim Berners-Lee proposal of the Web where the “people do the creative work and the machine does the administration”1. Setting out to challenge this, Rowland-Campbell argued that the balance between “man” and “machine” is changing, and the idea of humanity is changing as a result. In her talk she provides a number of suggestions on how this symbiotic relationship between man and machine may play out. 

1 Berners-Lee, T and Fischetti, M, Weaving the Web: The original design and ultimate destiny of the World Wide Web, Harper Collins, New York, 1999.

WST Managing Director honoured on Ada Lovelace Day

Professor Dame Wendy Hall receiving the Suffrage Science Award at Bletchley Park
Professor Dame Wendy Hall receiving the Suffrage Science Award at Bletchley Park/Sue Black ©2016

WST Managing Director, Professor Dame Wendy Hall, has received a significant award that honours women in maths and computing.

Professor Hall is one of 12 women to receive a Suffrage Science Award today (11 October) to celebrate their scientific achievements and ability to inspire others, at a special event at Bletchley Park. The event coincides with Ada Lovelace Day, an international celebration of the achievements of women in science, technology, engineering and maths (STEM).

Professor Dame Wendy Hall said: “I’m deeply honoured to receive this award amongst other extraordinary women in maths and computing. However, I remain frustrated by the need for such schemes as Suffrage Science to exist. It will only change if it becomes everyone’s issue and not just a women’s issue. We need to get the language right, which is we’re top scientists, not top women scientists”.

Women make up no more than four in ten undergraduates studying maths (London Mathematical Society), and fewer than two in ten of those studying computer science (WISE report, 2014).