PADAC&amp;#x2041;2: Real-time news recommendation system with heterogeneous social footprints

In the recommender systems field, it is increasingly recognized that focusing on accuracy measures is limiting and misguided. Unsurprisingly, in recent years, the field has witnessed more interest in the research of values “beyond accuracy.” This trend is particularly pronounced in the news domain where recommender systems perform parts of the editorial function, required to uphold journalistic values of news organizations. In the literature, various values and approaches have been proposed and evaluated. This paper reviews the current state of the proposed news recommender systems (NRS). We perform a systematic literature review, analyzing 183 papers. The primary aim is to study the development, scope, and focus of value-aware NRS over time. In contrast to previous surveys, we are particularly interested in identifying the range of values discussed and evaluated in the context of NRS, and embrace an interdisciplinary view. We identified a total of 40 values, categorized into five value groups. Most research on value-aware NRS has taken an algorithmic approach, whereas conceptual discussions are comparably scarce. Often, algorithms are evaluated by accuracy-based metrics, but the values are not evaluated with respective measures. Overall, our work identifies research gaps concerning values that have not received much attention. Values need to be targeted on a more fine-grained and specific level.

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PADAC⁁2: Real-time news recommendation system with heterogeneous social footprints

Cited by 2 publications

References 4 publications

Personalized News Recommendation based on Multi-agent framework using Social Media Preferences

Personalized News Recommendation based on Multi-agent framework using Social Media Preferences

Where Are the Values? A Systematic Literature Review on News Recommender Systems

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