2012-11-13: Cognoto pitch


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2012-11-13: Cognoto pitch

  1. 1. Identifying online malicious content cognoto.com
  2. 2. The Big ProblemHave you ever read a New York Timesarticle and then looked at thecomment section in the hopes offinding a thought-provokingdiscussion only to be let down by thehundreds of posts of profanity lacedwith rants and personal attacks?
  3. 3. The Big Problem1. The web has become flooded withdestructive posts that ruin the userexperience2. Companies have to employ moderatorseither in house or outsourced to prescreenUser Generated Content (UCG) like comments
  4. 4. Scientific AmericanJuly 25th, 2012These days, online comments "are extraordinarilyaggressive, without resolving anything," said Art Markman, aprofessor of psychology at the University of Texas at Austin….“Media outlets should cut down on the anger and hatredthat have become the norm in reader exchanges.”"If on a website comments are left up that are makingpersonal attacks in the nastiest way, youre sending themessage that this is acceptable human behavior." http://www.scientificamerican.com/article.cfm?id=why-is-everyone-on-the-internet-so-angry
  5. 5. BBCSept. 14, 2011“Trolling is a phenomenon that has swept across websitesin recent years. Online forums, Facebook pages andnewspaper comment forms are bombarded withinsults, provocations or threats.”“The answer is for newspaper websites and onlineforums to employ sufficient moderators to prevent thecomments spiraling into petty vendettas” www.bbc.co.uk/news/magazine-14898564
  6. 6. Reputation Users Online Community Participants in the Brand Community Authority Content Creators Toxic PostMedia Partners Other Stakeholders Observers in the Community Future Participants Advertisers
  7. 7. The Moderation MarketSome companies, including The New York Times andHuffington Post, still moderate their own websites,but the costs of employing full-time moderators canadd up.Often, a brand will simply abandon control of theircomments; Npr.org hired ICUC last year to manage allits commenting. www.businessweek.com/magazine/comment-moderator-the-dirtiest-job-on-the-internet-12012011.html#p2
  8. 8. The Moderation MarketModeration outsourcing services will continue to grow,predicts Jeremiah Owyang, an analyst specializing in onlinecustomer service with the Altimeter Group.Community Management firms charge clients up to $50k permonth for moderation servicesIndividual Moderators can earn $40k-$80k per year www.businessweek.com/magazine/comment-moderator-the-dirtiest-job-on-the-internet-12012011.html#p2
  9. 9. The SolutionTo help communities more efficiently manageuser generated content through acustomizable service that analyzes word andphrase patterns. (Semantic Analysis)Ability to place UGC into categories and canprovide a score of how confident the engine isof that placement
  10. 10. Training Testing 1 2Good Bad Known "Good" to Known "Bad" to us. us. Unknown to Unknown to "Cognoto" "Cognoto"
  11. 11. Who Are Our Customers?Providers of User Generated Content- Media Sites with comment sections including HuffingtonPost, NYTimes, Youtube- Retail sites with Product Reviews including Amazon,Newegg, eBay, and Zappos- Misc. including Yelp and Google MapsContent Management Service Providers such asDemand Media, LiveFyre, or DisqusFact Check: Huffington Post has a team of nearly 30moderators that look after more than 9 million pieces ofuser generated content (comments) each month!
  12. 12. Business ModelB2B ServiceWe provide content providers (like NYTimes,Huffpost) with a tool to help manage usergenerated contentProvide scalable but customized solution
  13. 13. Thank You!contact@cognoto.com cognoto.com
  14. 14. Experiment Looking at key words will not always give you the proper insight. ...Thats my business idea, but I am still having some doubts. Do guys think that is a stupid idea? That is not stupid. That is f***ing awesome. That is f***ing stupid. That is not awesome.
  15. 15. Think classifying by words is easy? Think again. Simple +/- keyword analysis +1 x +1 = +1 -1 x +1 = -1 -1 x -1 = +1 "good" +1 "bad" -1 "not good" -1 "not bad" +1 "no, that is not good" +1 wrong "no, that is not bad" -1 wrong "yeah, right" +1 wrong
  16. 16. Lorem ipsum dolor sit amet, consectetur adipiscing elit. G BGood vs Bad A B C D E = Bad 60% 40% 45% 53% 54% A - Proprietary Method B - Unigram C - Bigram D - Trigram E - Naive Bayes Classifier ...