[Priberam ML Seminars] Priberam Machine Learning Lunch Seminar (T12) - 7 - "Revealing semantic and emotional structure of suicide notes", Sofia Teixeira (Hospital da Luz Learning Health)

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Pedro Ferreira

Jun 8, 2021, 1:29:00 PMJun 8
to isr-...@isr.tecnico.ulisboa.pt, si...@omni.isr.ist.utl.pt, priberam_...@googlegroups.com

Hello all,

Hope you are all safe and healthy. The Priberam Machine Learning Seminars will continue to take place remotely via Zoom on Tuesdays at 1 p.m.

Next Tuesday, June 15th, Sofia Teixeira, Research Scientist at Hospital da Luz Learning Health will guide us through her work "Revealing semantic and emotional structure of suicide notesat 13:00h (zoom link: https://us02web.zoom.us/j/82692181898?pwd=QTlyU0dmRHpTSVdacWJrQmtKTi9XQT09 ).

You can register for this event and keep watch on future seminars below:
Please note that the seminar is limited to 100 people and this will work on a 1st come 1st served basis.

Best regards,
Pedro Ferreira

Priberam Labs

Priberam is hiring!
If you are interested in working with us please consult the available positions at priberam.com/careers. 

Image result for priberam logoPRIBERAM SEMINARS   --  Zoom 826 9218 1898

Priberam Machine Learning Lunch Seminar
Speaker:  Sofia Teixeira (Hospital da Luz Learning Health)
Venue: https://us02web.zoom.us/j/82692181898?pwd=QTlyU0dmRHpTSVdacWJrQmtKTi9XQT09
Date: Tuesday, June 15th, 2021
Time: 13:00 
Revealing semantic and emotional structure of suicide notes
Understanding how people who commit suicide perceive their cognitive states and emotions represents a crucially open scientific challenge. We build upon cognitive network science, psycholinguistics, and semantic frame theory to introduce a network representation of suicidal ideation as expressed in multiple suicide notes. By reconstructing the knowledge structure of such notes, we reveal interconnections between the semantic ideas and emotional states of people who committed suicide through structural balance theory, semantic prominence, and emotional profiling. Our results show that suicide notes have a higher degree of balance than one would expect in a linguistic baseline model capturing mind-wandering in absence of suicidal ideation. This is reflected in a positive clustering where positively perceived concepts are prominently central and are found to cluster together, reducing contrast with more peripheral and negative concepts. Combining semantic frames with emotional data, we find that a key positive concept is “love” and that the emotions populating its semantic frame combine joy and trust with anticipation and sadness, which can be linked to psychological theories of meaning-making as well as narrative psychology. Our results open new ways for understanding the structure of genuine suicide notes and may be used to inform future research on suicide prevention.
Short Bio:
Sofia Teixeira holds a PhD in Information Systems and Computer Engineering from Universidade de Lisboa (Portugal). Currently, she works as a research scientist at Hospital da Luz Learning Health in Lisbon. Previously, she was a postdoc at the Indiana University Network Science Institute. Sofia's research interests include modelling and analyzing complex systems through the development of new algorithms on graphs and the application of network science and machine learning methods.

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