There is not much information available when making split-second decisions whether to close or reopen a post. Specialist fields can limit the ability for a Close Voting User to accurately close a post.
For example, meet Bob. Bob is near retirement age and has 40 years of experience in software development. He likes the idea of StackOverflow and is thinking about becoming a major contributor when he retires. He spends 10 minutes crafting a clear precise question after not finding an answer on StackOverflow. He posts it and it is practically immediately closed as duplicate. Bob knows it's not, and with very little understanding of the culture and rules, he decides to quit StackOverflow, and pursue a leisurely life of live art performances underwater with blooms jellyfish. Such a loss.
Incorrectly closed posts have an adverse impact on novice (and experienced) users who humbly reach out, but don't know the rules, or are simply misunderstood.
There are probably a few ways to improve these "information famine" and "impaired experience" problems. Any feature that can measure these problems, or word toward reducing the impact are great advancements to the community culture.
The collection and display of more data points on a post provide Close Voters with more context to make more informed decisions quickly.
Bob's life could have been more enriched with StackOverflow. Instead of closing the question, a Close Voter might have instead decided to add a comment. "Welcome to SO, it looks like your question is similar to X, I can see you spent 30 minutes searching for answers, and 10 minutes writing the post, please help me understand how your question is different so I don't vote to close it"
If we implement this, we can rescue Bob from the ocean.
- it could be the total amount of time that the user has the tab active.
- it could involve the most amount of seconds that the user was typing for.
- it could also model the typing speed (I type up to ~100 wpm).
- it could also factor in time of a user over multiple edits and report the total time.
- it could factor in time on the site before the user was "searching" before posting
- it could indicate if the user scrolled through close matches while typing the title
- it could include search terms used while searching, where they match content in the post, to show how the user searched for duplicate items
- it could include URLs the user visited when they were searching that have matching terms