As Ted asserts, the interview is brilliantly edited and, “presents a seamless train of thought selected from my sweeping complex of ideas”. For an introduction to the thinking of the pioneering inventor of Hypertext, it’s well worth viewing.
Lo and Behold is available in full on Netflix and Amazon Prime.
The Internet on Film – 2016
The year the Walker Art Center finally lowered the curtain on the Internet Cat Video Festival* also featured the release of some notable Internet-related films:
Web Science Trust Board member, John Taysom writes on the Importance of Data Governance, with Special Reference to Finance in a recent Royal Society and British Academy publication. The report, Connecting debates on the governance of data and its uses, brings together contributions from leading representatives from academia, government and business; including experts in ethics, law, finance, social and data sciences, machine learning and statistics in order to build connections between existing debates, and identify key questions and gaps.
The Academies have initiated a project examining new uses of data and their implications, and reviewing the data governance landscape. The project will make recommendations for cross-sectoral governance arrangements that can ensure the UK remains a world leader in this area.
For the Web to succeed, we need to understand its societal challenges including increased crime, the impact of social platforms and socio-economic discrimination, and we must work towards fairness, social inclusion, and open governance.
Web Science is even more important now than it was when the field was launched ten years ago, say Professors Dame Wendy Hall, Jim Hendler, and Steffen Staab in our Web Science Manifesto, published earlier this week at WebScience@10.
While recognising the huge influence the Web has had on our lives since its foundations were defined by Tim Berners-Lee 27 years ago, the Hall, Hendler, and Staab focus their attention on how Web Science tackles the unforeseen social outcomes of this era-defining technical innovation. They discuss the digital divide that separates those who have and those who do not have access to the Web – the challenges we must understand to find a viable balance between data ownership and privacy protection, and between over-whelming surveillance and the prevention of terrorism.
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.
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.