The normal state of news is that a story breaks and there are 300 near identical articles about it in 24 hours. Google News wouldn't have been successful if they hadn't developed a clustering algorithm that handles this.
Ordinary clustering algorithms don't work well for documents period in my experience and I am not sure if that's the right approach to topic identification. But if we're going to get past RSS readers having the same failing interface that has been failing since 1999 and get past the idea that social media is bad because "algorithms = bad" we need some algorithm to tame the many "me too" blog posts that come whenever a blog post breaks onto the front of HN.
What exactly are "we" supposed to do about it?