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Balance: Facebook Project Journalism Hackathon

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Learn how two emerging technology specialists created ‘Balance’ – a news service which provides a cross publisher view on similar and opposing articles.

Anna Thomas and Dan Cunnington from Emerging Technology attended the event in London and the day kicked off with a panel discussion from various companies within the media industry. The panel included Jon Heaton – Partner Engineer at Facebook, Yusuf Omar – Senior Social Reporter at CNN, David Milne – Head of Digital Publishing at STV and Andrew Mullaney – CTO of Newswhip. The panel discussed upcoming trends within the media industry, such as emerging storytelling formats and live streaming. It was really interesting to hear thoughts around the use of Virtual and Augmented Reality and how that will affect publishers in terms of the ability to analyse, process and display content to users. This highlighted the need for new ways of exploring news content, moving away from the traditional article based format. Fake news was a hot topic, with all members of the panel explaining the scale of the problem and also the technical difficulty.

Teams then began to brainstorm around the challenges discussed and it was here that ‘Balance’ was born. Fake news is a big problem and users are losing the ability to trust pieces of content they read online or in the media. Users can often be influenced by articles that play on emotional triggers or portray certain entities/characters in a certain way. For an end user, It can be difficult to see a balanced view of the news surrounding a particular topic and news platforms such as Facebook wish to remain impartial on the content they display. ‘Balance’ aims to provide a cross publisher, cross platform view of news content related to a specific topic. As the hackathon coincided with the day Theresa May officially triggered Article 50, we focused our prototype on the topic of ‘Brexit’ in order to collect recent content. ‘Balance’ captures social data from CrowdTangle (http://www.crowdtangle.com/) and articles from the IBM Watson Discovery News Service (https://www.ibm.com/watson/developercloud/discovery-news.html ). Using the traditional article based format alongside emerging social formats allows a broad view to be generated of news content surrounding a particular topic.



With news data flowing from two services, we then analysed the entities and emotional sentiment of the articles using the IBM Watson Alchemy Language (https://www.ibm.com/watson/developercloud/alchemy-language.html ) service, taking inspiration from Zoe Lanham and Dominik Ullmann with their Trump vs Clinton comparison at the ETS December hackday. This allowed us to identify certain entities or topics and have a sentiment score associated with that topic for ‘Anger’, ‘Fear’, ‘Disgust’, ‘Joy’ and ‘Sadness’ emotions. If an article is in favour of Brexit, we’d expect to see a negative score for ‘Disgust’ and ‘Sadness’ as well as a positive score for ‘Joy’. With this data, we can then recommend similar and also opposing articles to give the user a balanced view of the news.



This helps to reduce the impact of fake or manipulative news, as the user can see the full picture on both sides of an argument and it also helps to discover new content from sources they would not normally follow.

To build the app we used Node-RED (a visual programming tool to quickly wire together different API’s http://nodered.org/ ) and also Angular.js to display the data in a visual and meaningful manner.

To check out the demo, please visit the following URL: http://balance.eu-gb.mybluemix.net/



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thanks for sharing.

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