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Say you had a great experience at a coffee shop- you post [satisfied] towards [Velo Rouge Cafe]. If enough people do this, anyone who wants a quick snapshot of
by jiganti 15y ago
Say you had a great experience at a coffee shop- you post [satisfied] towards [Velo Rouge Cafe]. If enough people do this, anyone who wants a quick snapshot of what people have experienced in Velo Rouge might just search for them on Moodstir. If there are a lot of [satisfied] emotions posted, or a lot of [frustrated] ones, it imply certain things about the cafe. Different than a Yelp review site, in that it takes the aggregate feelings of all users, rather than a simple X/5 star system, which is a more limited glimpse into peoples' experiences.
- thhaar 15y agoI get it, and dig it. Aggregating moods would be useful on a site such as Amazon, where, depending on the technical level of the product, reviews range from sharp and intelligent to blunt and kneejerk. Having access to sentiment analysis would help consumers to quickly see whether or not the product/service being 'mood reviewed' solves their problem or not. Written reviews are full of conjecture and anecdotes, 5-star gradings may as well not exist for 2-4 stars, so mood is another great metric to add to these tools.
- gradstudent 15y agoI still don't get it: moodstir has no context such as you describe. There's no reason I'd go there to post cafe reviews nor would I visit the site expecting to find such. Near as I can tell what you have here is a micro-blogging app whose functionality is entirely dominated by existing services. I'm not trying to troll here: I genuinely think it's important for you to have convincing responses to this kind of critique.