Future of News: Journalist ORCID and News Article Quality Metrics

Credible Web Community Group,



Here is a quick outline of some ideas pertaining to mitigating misinformation and disinformation online, improving online news quality, journalist ORCID, news article quality metrics, news aggregators, search engines, and recommender systems, and machine learning:



  1.  Journalist ORCID.
  2.  Hindsight news article quality metrics.
     *   Was a news article, in hindsight, factually accurate?
        *   Was a news article, in hindsight, corroborated by other news articles, e.g., an article cluster?
     *   How can news article clusters and story threads be of use for computing hindsight quality measures?
        *   Beyond article similarity, what other typed links between news articles might be useful?
           *   Might some topic-based or similarity-based news article clusters contain subclusters with news articles having differing scores per sentiment analyses, ideology analyses, values analyses, and so forth?
     *   Did readers enjoy a news article, directly, e.g., by pressing a thumbs-up or button, or indirectly, e.g., by other usage behaviors?
     *   Was a news article, in hindsight, popular, e.g., shared on social media?
  3.  Predictive news article quality metrics.
     *   How can some predictive article quality metrics for new news articles be derived from hindsight metrics and data, e.g., metrics pertaining to those organizations and individuals publishing a new news article?
     *   How can other technologies, e.g., natural-language processing, natural-language understanding, knowledgebases, and automated reasoning, be of use for predicting quality metrics for new news articles?
        *   How might such technologies be of use to journalists, as products, for presenting analytics before they publish a news article?
  4.  News aggregators, search engines, and recommender systems.
     *   How can combinations of hindsight and predictive metrics of news article quality be of use to news aggregators, search engines, and recommender systems?
  5.  Machine learning from human curation.


Any thoughts about any of these topics? Thank you.


Best regards,

Adam Sobieski