Amazon Comprehend

Discover insights and relationships in text

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#2 Product of the DayNovember 30, 2017

Amazon Comprehend is an NLP service that identifies the language of the text; extracts key phrases, places, people, brands, or events; understands how positive or negative the text is; and automatically organizes a collection of text files by topic.

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Reviews

 +7 reviews
  • John GilArchipella Studios (Owner)
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    Cons: 

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    Allowing robots to do your creative thinking is an arena for the lazy and vulnerable mind. Of course this will not be understood now because all things new are exciting and the youth of today are unwittingly being drawn into a false collective. The day will come when a significant aspect of the individual identity, the very point of existence, is no more and the individual will lack the self cognizance to ask this question due to unawares. What remains at that point is obedience, a goal that the globalists of the war have been seeking for many centuries. Well done! Everyone has played their role to perfection. My friends remain the anomalies.

    John Gil has never used this product.

Discussion

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Charlie Coppinger@thecoppinger · Managing Director @ Arcane Strategy
I spent a few minutes trying to figure out how this might be useful from a marketing perspective, and here's what I came up with: I recently came across a copy-writing 'hack' of sorts, which involves collecting a large number of negative reviews from a similar product/service to which you are attempting to write sales copy for and using a simple word-density analyser to determine which are the main pain-points that the feedback revolves around. That way, in theory, you can ensure that you're speaking to your audiences actual pains, as opposed to your assumptions of what they are. This could be used for the same purpose, only on steroids 💪🏼
David J. Bradley, MBA@dbradleyri · Digital Marketing Strategy Expert
@thecoppinger Exactly the perspective I was looking at this with. Now, I'll wait for someone to list an iteration of this with their own tool that does that specifically...
Scott BowlerPro@scotty_bowler · ChooseHolly.com lowcost social schedules
Here's a screenshot of what Amazon Comprehend looks like/does by the way: https://imgur.com/a/h5H2X Can't wait to experiment with this on www.chooseholly.com - could provide enormous benefit and insights for our users
Samuel RoyPro@samuelroy_ · Co-founder & CTO @botmatic.ai
Other providers like Recast.ai and Wit.ai are great at this too. See how Recast automatically find entities like Amazon and even identify "north" and "south": https://imgur.com/a/tD0kn This is what we use for https://producthunt.com/upcoming..., working well I can tell you!
Kristian FreemanPro@imkmf · Maker, software engineer and synth nerd
If you'd like to play with this technology locally, Stanford CoreNLP is a great open-source framework (GPL license) for NLP processing: https://stanfordnlp.github.io/Co...
Brennan ErbeznikPro@brennanerbz · Product Designer, Snap
@imkmf Let's see a performance comparison.
Martin H. Normark@martinhn · Founder, @geteighty
Jacob WallenbergPro@jrwallenberg · Working on SolutionLoft
@imkmf @brennanerbz @martinhn I've played around with a few different packages (CoreNLP + some derivatives, Indicoio, etc.) and was very pleased with the keyword and sentiment features of Comprehend. The sentiment feature especially seems far more accurate.
Brennan ErbeznikPro@brennanerbz · Product Designer, Snap
@imkmf @geteighty @jrwallenberg what’s remarkable is that not much has changed since the 1990s when the Stanford parser was born. We’re still only doing basic entity and sentiment analysis. Where’s the meaning?
Jacob WallenbergPro@jrwallenberg · Working on SolutionLoft
@imkmf @geteighty @brennanerbz I can't speak for how sophisticated it was back then, but I find this stuff super helpful. I can barely write Python, but I'm able to automatically parse through thousands of customer reviews and extract what they're talking about and how they feel about it with a decent level of accuracy - using completely free resources!
Sebastian Dobrincu@sebyddd · Serial Product Maker. I turn💡 to 💰
This has the potential to make NLP somewhat more mainstream among tech companies. Curious to see what the adoption will look like.
Donte Ledbetter@donte_ll · Marketing Manager at Stash
This is very neat!