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I wish the person who mapped the Russian twitter bot network [1] would take a gander at Amazon reviews/reviewers. I used to depend on Amazon overall star rating

I wish the person who mapped the Russian twitter bot network [1] would take a gander at Amazon reviews/reviewers. I used to depend on Amazon overall star rating, but these days scrutiny of the single-star reviews is required to detect the many cheaters. Note that this includes a bunch of "invitation only" Vine program participants. Reported a few, nothing ever came of it. [1] http://globalvoicesonline.org/2015/04/02/analyzing-kremlin-twitter-bots/ http://globalvoicesonline.org/2015/04/02/analyzing-kremlin-t...

walterbell 12y ago
This would require a review API, which seems to be missing, http://stackoverflow.com/questions/4811259/is-there-an-amazon-com-api-to-retrieve-product-reviews http://stackoverflow.com/questions/4811259/is-there-an-amazo... Edit: see also https://www.npmjs.com/package/amazon-reviews https://www.npmjs.com/package/amazon-reviews
- motdiem 12y ago
  Yep - a review API is sorely missing - we've built a tool to enable reviewers to download their own reviews [1], and had to workaround many weirdness in the review system. I would say that besides obvious fraud detection, it is an under-managed part of amazon, with a lot of semi-rational behaviour from reviewers, because no one is sure what amazon actually does with those. Reviews routinely disappear, reappear on a whim - how you get to vine is not clearly understood. We've actually gathered a few interesting data on this topic, I should probably put a blog post about it sometime.... [1] https://reviewers.mediapps.com/ https://reviewers.mediapps.com/
  - notlisted 12y ago
    Haha, are you and walterbell tag-teaming? (see above) That would be ironic.
    - walterbell 12y ago
      Where's that HN comment API :)
    - motdiem 12y ago
      ha didn't see this edit before I commented - we haven't released the code , but I'll have a look at the node package mentionned above, maybe I can contribute a bit :)
    - deleted 12y ago
      [deleted]
- notlisted 12y ago
  I know, wishful thinking. A little scraping might go a long way. If the data were available, I'm certain the networks could be easily identified by clustering the overlap on 5 star reviews of totally unrelated items. e.g. I noticed a highly unlikely overlap between multiple reviewers of a particular hardware product my wife had mistakenly bought. When reviewing how she could have made this mistake, I discovered the title was misleading and the many 5 star reviews were fake. Looking at 5 star reviewers history showed a bunch who shared reviews of completely different items (in the make-up/food supplement arena) all produced by the same manufacturers.
nick_wikilerts 12y ago
I second the "these days scrutiny of the single-star reviews is required". The knowledgable internet user is aware that it's the 1-star reviews which tell the truth (at least most of the time).
- mcguire 12y ago
  Perhaps. I usually go for the three star reviews and actually read the comments.
- walterbell 12y ago
  Thoughtful/erudite 5-star reviews and most 1-star reviews carry useful, distinctive signals. References to related books can be used to calibrate reviewer taste.

walterbell 12y ago

This would require a review API, which seems to be missing, http://stackoverflow.com/questions/4811259/is-there-an-amazon-com-api-to-retrieve-product-reviews http://stackoverflow.com/questions/4811259/is-there-an-amazo... Edit: see also https://www.npmjs.com/package/amazon-reviews https://www.npmjs.com/package/amazon-reviews

motdiem 12y ago
Yep - a review API is sorely missing - we've built a tool to enable reviewers to download their own reviews [1], and had to workaround many weirdness in the review system. I would say that besides obvious fraud detection, it is an under-managed part of amazon, with a lot of semi-rational behaviour from reviewers, because no one is sure what amazon actually does with those. Reviews routinely disappear, reappear on a whim - how you get to vine is not clearly understood. We've actually gathered a few interesting data on this topic, I should probably put a blog post about it sometime.... [1] https://reviewers.mediapps.com/ https://reviewers.mediapps.com/
- notlisted 12y ago
  Haha, are you and walterbell tag-teaming? (see above) That would be ironic.
  - walterbell 12y ago
    Where's that HN comment API :)
  - motdiem 12y ago
    ha didn't see this edit before I commented - we haven't released the code , but I'll have a look at the node package mentionned above, maybe I can contribute a bit :)
  - deleted 12y ago
    [deleted]
notlisted 12y ago
I know, wishful thinking. A little scraping might go a long way. If the data were available, I'm certain the networks could be easily identified by clustering the overlap on 5 star reviews of totally unrelated items. e.g. I noticed a highly unlikely overlap between multiple reviewers of a particular hardware product my wife had mistakenly bought. When reviewing how she could have made this mistake, I discovered the title was misleading and the many 5 star reviews were fake. Looking at 5 star reviewers history showed a bunch who shared reviews of completely different items (in the make-up/food supplement arena) all produced by the same manufacturers.

nick_wikilerts 12y ago

I second the "these days scrutiny of the single-star reviews is required". The knowledgable internet user is aware that it's the 1-star reviews which tell the truth (at least most of the time).

mcguire 12y ago
Perhaps. I usually go for the three star reviews and actually read the comments.
walterbell 12y ago
Thoughtful/erudite 5-star reviews and most 1-star reviews carry useful, distinctive signals. References to related books can be used to calibrate reviewer taste.