[eevilspock]

I love the fact that the ratings are semantic, and limited to four easy to understand values rather than 5 stars:

    Awful (Can I have those two hours back?)

    Meh (Not great, but better than nothing 
         to kill time, escape or veg out)

    Good (I enjoyed watching it)

    Amazing (I'd watch it again and recommend
             it to friends without hesitation)

With 5 stars, everyone interprets 2, 3 and 4 stars differently, e.g.:

    Horrible  Bad  Meh   Good       Best

    Bad       Meh  Good  Very-Good  Faves

Even the same person over time will not use a 5-star scale consistently. Even when I try to be consistent (I use the latter values for Netflix), if I like a movie but don't love it I don't know whether to give it 3 or 4 stars. On different days in different moods I'll make different choices.

I've no doubt that unreliable ranking data made Netflix recommendations harder, and impacted their mix of recommendation algorithms -- i.e. leaning more heavily on those that work despite rating scale inconsistencies. I'd expect the mix that works best for Taste.io will be different.

[sqtomato]

I have to agree that the rating options are very refreshing and easier to keep consistency over time. It also forces a choice between positive and negative which I'd imagine helps the algorithm learn things faster. Hmm...