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I4ADA 2019 - presentatiob oleg volkosh

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See https://i4ada.org for additional information and videorecordings of the presentations held at the Hague Summit for Accountability in the Digital Age

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I4ADA 2019 - presentatiob oleg volkosh

  1. 1. 18 206 SUICIDES 2 * SOURCE: Russian Statistic Committee 2018 ≈ 19 092 TRAFFIC ACCIDENTS
  2. 2. SUICIDES PER MONTH ~1 500 CALLS ON A HOTLINE PER MONTH ~3 800 MESSAGES ONLINE ABOUT INTENSIONS OF SELF- HARM PER MONTH ~10 000 «…I need help, but nobody answered the phone …they answered only on the third time» *SOURCES: Russian Statistic Committee, 2018 Department of labor and social protection of the population of Moscow, 2018 Brand Analytics Monitoring System, August-July 2019
  3. 3. 4 100 MLN PEOPLE 38 097 29 551 23 771 22 340 11 068 5 185 Vkontakte Instagram Odnoklassniki Facebook LiveJournal Mail.ru // My world AUDIENCE PER MONTH * SOURCE: Mediascope , Web Index, September 2019, Monthly Reach% and thousands people, All 69% 12% 9% 6% 3% 1% SOURCES WHERE SUICIDE WAS MENTIONED vk.com youtube.com instagram.com facebook.com ok.ru otvet.mail.ru
  4. 4. 5 younger than 18 y.o. 18 – 24 y.o. 25 – 34 y.o. 35 – 44 y.o. 45 – 54 y.o. 55 y.o. and older USERS WHO MENTIONED AN INTENTION TO COMMIT SUICIDE ON SOCIAL MEDIA (DISTRIBUTION BY AGE) 692 children committed suicide in 2017, 788 in 2018 14% SOURCES: Russian Investigating Committee, 2018 Brand Analytics Monitoring System, August-July 2019
  5. 5. 6 * SOURCE: Brand Analytics Monitoring System, 2019 … AND BEFORE THEY KILLED THEMSELVES, THEY WROTE ABOUT IT ON THE INTERNET.
  6. 6. INTERACTION DETECTION OF SUICIDE INTENTIONMONITORING &ANALYSIS MACHINE LEARNING COLLECTING SML BIG DATA SEARCH QUERIES TESTING • Identified threads are sent to the specialists for immediate interaction • Or a moderator with the qualification of a psychiatrist is embedded in the dialogue to provide first aid • Specially trained moderators explore conversations and threads in real time, in order to identify potential suicide victims • Automatic detection of the tone when mentioning suicide with an accuracy of 85-90% • Human analysis • Machine-learning algorithms categorize messages, identify media field trends, aggression, recognize texts on images, etc. • Data collection on the Internet: social media, forums, blogs, video hosting, review sites, media, open chats in messengers • Preparation and testing of the linguistic query with various word forms, meanings and specific terms linked to suicide, including depression, loneliness etc. 7
  7. 7. 8 1. WE SHOULD BE IN PLACES WHERE PEOPLE DISCUSS IT 2. WE SHOULD BE THERE BEFORE THEY MAKE A DECISION 3. WE HAVE TO PREVENT IT WHEN POSSIBLE, USING MARKETING AND AI TECHNOLOGIES

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