{"id":85118,"date":"2023-09-10T12:02:11","date_gmt":"2023-09-10T09:02:11","guid":{"rendered":"https:\/\/www.technion.ac.il\/blog\/suicide-prevention-hackathon\/"},"modified":"2023-09-10T12:02:11","modified_gmt":"2023-09-10T09:02:11","slug":"suicide-prevention-hackathon","status":"publish","type":"post","link":"https:\/\/www.technion.ac.il\/en\/blog\/suicide-prevention-hackathon\/","title":{"rendered":"Suicide Prevention Hackathon"},"content":{"rendered":"

Every 40 seconds, someone, somewhere in the world is taking their own life. In Israel alone, 500 people die by suicide every year. In 2003, the International Association for Suicide Prevention, in conjunction with the World Health Organization (WHO), chose September 10 to be World Suicide Prevention Day, aiming to focus attention on the issue, reduce stigma and raise awareness. What can be done that hasn\u2019t been tried already, to find these people, and offer them help in time?<\/p>\n

\u201cWe have the tools to try and help,\u201d says Dr. Shiri Daniels, Professional Director at ERAN<\/strong>, Israel\u2019s Emotional First Aid service. \u201cBut even professional psychologists struggle to recognise suicidal ideation ahead of time. In retrospect, those close to a suicide victim often say there were signs. But then and there, they couldn\u2019t recognise those signs.\u201d<\/p>\n

Can AI tools help put together the signs that slip under the radar? \u201cPeople put more of themselves on social media than they realise,\u201d says Prof. Avigdor Gal from the Technion \u2013 Institute of Technology Faculty of Data and Decision Sciences<\/strong>. “In a three-day hackathon, students of the faculty tackled the challenge, looking for ways to recognize suicidal ideation and offer assistance. The hackathon is always dedicated to helping with a specific social issue. We cannot be blind to society around us, what is done with the tools we develop, how the data we collect is used. Our values must be part of the work we do.\u201d<\/p>\n

Hackathons are an opportunity for students to gain hands-on experience tackling the kind of challenges they would face in their future careers. In that vein, Bachelor\u2019s students from all study tracks (Industrial Engineering and Management; Information System Engineering; Data Science and Engineering) at the Faculty of Data and Decision Sciences take part in the department\u2019s annual hackathon.<\/p>\n

This year, 70 students, split into 16 teams, took part in the event, each comprising students from different years and tracks. Each team was given $50 to use on GPT API, offering students an opportunity to get familiar with the tool, as well as to learn budget management.<\/p>\n

The data used in this hackathon is part of the research of Ph.D. student Shir Lisak and M.Sc. student Ilanit Sobol, who both work on recognising suicidal behaviors online under the supervision of Prof. Roi Reichart in the Natural Language Processing (NLP) lab at the Faculty of Data and Decision Sciences.<\/p>\n

\"First<\/a>
First place winners<\/figcaption><\/figure>\n

First place went to Ziv Barzilay, Liad Domb, Omri Lazover, and Jonathan Wolloch, who proposed a system that would use information gathered from social media to target the inner circle of individuals displaying suicidal ideation with ads and banners related to the subject. The team\u2019s hope is that those closest to the individuals at risk would be more aware of, and sensitive to, the signs which come before acts of self-harm, and would be best positioned to help.<\/p>\n

\"Second<\/a>
Second place<\/figcaption><\/figure>\n
\"Second<\/a>
Second place<\/figcaption><\/figure>\n

 <\/p>\n

Two teams tied for second place. Idan Horowitz, Lian Fichman, Shir Geisler, and Ariel Cohen used facial expression identification and NLP tools to analyse the video and transcription of posted videos, providing real-time insights to mental health professionals about the emotional well-being and suicide risk of their patients, aiding their diagnosis.<\/p>\n

Ariel Novominsky, Alexander Freydin and Vladislav Comantany attempted to characterize the emotional process a person undergoes before deciding they want to commit suicide and proposed a quantitative measurement method for the abstract concept, an emotional process, in order to allows for mathematical analysis.<\/p>\n

\"Students<\/a>
Students during the event<\/figcaption><\/figure>\n

The Data for Good Israel, ERAN, Gila\u2019s Way and Bishvil Hahayim (Path to Life) associations enthusiastically joined the event and gave the students the information and motivation to develop solutions that may save lives in the future. With the help of these organizations, the students were able to approach the difficult subject of suicide with maximum information.<\/p>\n

No less importantly, they could begin to discuss this difficult and painful topic in an open and sensitive manner. Being alert to the signs of people suffering from suicidal ideation and signs of deterioration before taking action could, the organisations hope, be useful beyond the narrow scope of the Hackathon.<\/p>\n

The event was funded with the help of the, the Israel Data Science Initiative (IDSI), Technion Social Hub and Tech-AI.<\/p>\n","protected":false},"excerpt":{"rendered":"

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