• Eden Saig, a computer science student at the Technion-Israel Institute of Technology in Israel, developed the computerized learning system which works by recognising repeated word patterns. The system was constructed to identify key words and grammatical habits that were characteristic of sentence structure implied by the content's sentiments.
  • The quantification was carried out by examining 5,000 posts on social media pages and, through statistical analysis, gearing a learning system to recognize content structure that could be identified as condescending or slang.
  • "Now, the system can recognize patterns that are either condescending or caring sentiments and can even send a text message to the user if the system thinks the post may be arrogant. When applied to other networking pages it may help detect content that suggests suicidal ideations, for example, or 'calls' for help, or expressions of admiration or pleasure.” said Saig.

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