Here are some factors you should consider:
License: You said you didn't see a license, but the absence of a license doesn't mean it's free to use. It means you need to look harder. (Reviews are probably substantial enough to be covered by copyright law in most countries, too.) Try to find the form, or the Facebook users who circulated it, or something. (Try Googling for the text of one of the reviews to see where they've been published.)
If (hypothetically) Yelp harvested reviews from UrbanSpoon, it's a good bet that the latter would complain. So the first question you need to answer is whether you can use the data at all.
Assuming you can...
Data model: Will your web site allow a user to post multiple reviews of the same item? If not, then if you were to use a single aggregate user like crowd_from_web, you would have to build special cases into your code. Special-case code can be a sign that you're doing something that's not quite right in some fashion.
Aggregation only, or deeper data-mining? Could the plans for your web site ever include any sort of "users who liked X also liked Y" logic? If so, you'd be at least throwing valuable data away, and possibly messing up your data set besides, if you lump all the imported reviews together under one user. If the data has any way to tell users apart -- user numbers, for example -- then you're better off retaining it. It's easy to present it as a single source later if you decide you don't care about this at all, but you'll never be able to go back.
If the reviews are completely anonymous without even user numbers or the like, you're probably better off simulating one user per review instead of aggregating them. The user names you create for these imported quasi-users can reflect the source in some systematic way, and then you can give proper credit to your source in an "about" page or similar. ("Reviews posted by users with names of the form user_### were imported from such-and-such source.") Then use a slightly different pattern for newly-created users.
