Hackathon-Challenge-Pitch_221124.pdf

Transcript

1. Who?
   Research Project on «The Role of News Recommender Systems in Digital Democracies»
   Sina Blassnig1, Edina Strikovic2, Eliza Mitova1, Aleksandra Urman3,
   Anikó Hannák3, Frank Esser1, & Claes de Vreese2,
   1 Department of Communication and Media Research, University of Zürich
   2 Amsterdam School of Communication Research, University of Amsterdam
   3 Department of Informatics, University of Zürich
   Contact: s.blassnig@ikmz.uzh.ch
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2. Why?
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   – Changing user behavior – Increasing automation and personalization of
   news
   Source: Digital News Report 2022, Data for Switzerland
   

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3. What are News Recommender Systems (NRS)?
   – Algorithms that can make automated
   and/or personalized recommendations
   based on metadata, past behavior,
   ratings of similar users, popularity,
   and/or content-specific features (Ricci et
   al., 2011)
   – NRS can be used on the frontpage of
   news media websites, below articles,
   in special sections, for newsletters,
   etc.
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4. What is the problem?
   – Good NRS are expensive, laborious
   and complicated.
   – That’s why media still often focus only
   on:
   – Topic similarity
   – Popularity
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5. What is the Challenge?
   1) Analyze the problem:
   – What gets left behind if we focus on
   popularity-based recommenders?
   what categories, e.g., topics, regions, actors,
   formats etc. are over- or underrepresented
   2) Provide a solution:
   – What would need to be pushed in a
   diversity-maximizing recommender?
   what categories, e.g., topics, regions, actors,
   formats etc.
   – Can this be done in a transparent
   way? E.g., by showing why something is
   recommended
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6. Potential Resources & Needed Data
   Needed:
   − Content archive (articles, videos, audio)
   − Aggregated user data (e.g., likes, clicks,
   views, time spent)
   Available:
   - SRG APIs:
   https://developer.srgssr.ch/apis/
   - Others?
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7. Contact
   Sina BlassnigDepartment of Communication and Media Research, University of Zürich
   Contact: s.blassnig@ikmz.uzh.ch
    Slack
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