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Users will often be interested in only a subset of information (written by a specific person or persons, or covering a certain topic)*
- Why is the task being done? The user wants to restrict the given information to that subset.
- What does the user need to know or have before doing the task? They need to be logged in, and know enough about the subset to describe it or pick a filter.
- Where is the task performed? Either on a desktop/laptop, or on a phone browser.
- What is the environment like? Noisy, dirty, dangerous? It could be, if the user is on the go with their smartphone or tablet.
- How often is the task performed? This depends on the user’s profile; some may do it all the time, others only once or twice per session.
- What are its time resource constraints? The feedback loop should ideally be very fast, comparable with Google Instant Search, so that refining the filter is easy.
- How is the task learned? The user can learn it by recognition; we plan to design the interface so its controls are very similar to Google Instant Search or other similar mechanisms.
- What can go wrong? The filter could be incorrect (too broad or narrow), or it could have a typo. A fast feedback loop will improve safety by ameliorating these issues.
- Who else is involved in the task? No one else in this case.’
- What subtasks are there? Navigating to the textbox (or other form element used for filtering, entering the author name or topic to keep (or reusing an old filter), scanning the subset displayed, and revising the input if needed. Optionally, users could save the filter for future usage.
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