Recent concerns about filter bubbles, fake news and echo chambers are symptomatic of the disruptive potential of digital recommendations, but also demonstrate the need for responsible recommender design. News recommender systems, driven by data and machine learning, automatically select the content of newsletters, personalized news apps, or social media news feeds. Recommender systems can make or break filter bubbles, and as such can be instrumental in creating either a more closed or a more open internet. Much will depend on the design of news recommenders. Are they merely designed to generate clicks and short term engagement? Or are they programmed to balance short term engagement and relevancy with the legitimate longer term interest of users in diverse information and not losing out on important information?

To unlock the full potential of news recommenders, we need to create innovative metrics and measures that help to strike the right balance between short-term engagement and diversity. The key to such an endeavour lies in the effective operationalization of a rather imprecisely-defined societal concept – diversity -  into measures and metrics that can actually inform the design of recommenders. The aim of this proposal is therefore to translate research into diverse recommender design done at the University of Amsterdam into novel ways with which publishers and news aggregators can improve the performance of their algorithmic recommenders. We will develop a toolkit to automatically measure and externally judge the diversity of recommendations through the analysis of the recommended content. We will do so in cooperation with RTL and Blendle -  an innovative Dutch online news platform that offers access to articles from more than 100 publishers in the Netherlands, Germany and Belgium, and is a forerunner in experimenting with algorithmic recommendations. 

This project is made possible with a funding from the SIDN fonds.

You will:

• develop automated tools for analyzing content to measure diversity, and help to create a toolkit that automatically annotates media content on these measures;
• to this end, cooperate closely with the team from Blendle and RTL, and the researchers from the University of Amsterdam (media, communications science, data science) to operationalize several dimensions of diversity (e.g. topic diversity, frame diversity, discourse diversity, representativeness, etc.);
• experiment with the dimensions of diversity combined with different recommender metrics and develop a set of key performance indicators (KPIs);
• do real-life testing of the models developed;
• help to co-oordinate workshops and (international) outreach activities.

You should have:

• an advanced degree (e.g., master or PhD degree) in data science, or communication or other social science with outstanding data mining and analysis skills;
• active research knowledge of, and expertise in, modern search and text mining methods;
• experience in programming in Python (2.7/3.x);
• experience with Natural Language Processing (NLP) (e.g. Topic Modelling), Machine Learning experience is a plus;
• excellent oral and written communication skills;
• team spirit, willingness, and commitment to do autonomous work in a multidisciplinary team, including communication scholars, legal scholars, and data scientists.

Database handling experience, Git skills, Bash Scripting are considered pros.

The position preferably starts between 1 July and 1 September 2018. It concerns, in principle, a one-year period after an initial test period.

The monthly gross salary, depending on your knowledge and experience, will range between €2,588  and €4,757 (Scale 10/11) based on a full-time basis.

We offer a pension scheme, a holiday allowance of 8% per year, and an end of year allowance of 8,3% per year and flexible employment conditions. Our conditions are based on the Collective Labour Agreement for Dutch Universities.

University of Amsterdam

With over 5,000 employees, 30,000 students and a budget of more than 600 million euros, the University of Amsterdam (UvA) is an intellectual hub within the Netherlands. Teaching and research at the UvA are conducted within seven faculties: Humanities, Social and Behavioural Sciences, Economics and Business, Law, Science, Medicine and Dentistry. Housed on four city campuses in or near the heart of Amsterdam, where disciplines come together and interact, the faculties have close links with thousands of researchers and hundreds of institutions at home and abroad.  

The UvA’s students and employees are independent thinkers, competent rebels who dare to question dogmas and aren’t satisfied with easy answers and standard solutions. To work at the UvA is to work in an independent, creative, innovative and international climate characterised by an open atmosphere and a genuine engagement with the city of Amsterdam and society.

http://www.uva.nl/en/home

Amsterdam Law School

The Amsterdam Law School prides itself on its international orientation and strong social commitment. This is reflected by both its research and educational activities. We offer three Bachelor’s programmes and a variety of Master's, several of which are taught exclusively in English (i.e. International and European Law, European Private Law, International Criminal Law, and Law & Finance). Our School prepares students for a wide variety of legal careers including law firms, government, business and industry, the national and international judiciary, public service, human rights advocacy, and academia. With 3,500 students and over 400 staff members, we are one of the largest law faculties in the Netherlands. Our School is located in the centre of Amsterdam

http://www.uva.nl/en/faculties/faculteit-der-rechtsgeleerdheid/faculty-of-law.html