A deep learning approach for identifying cancer survivors living with post-traumatic stress disorder on Twitter
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RESEARCH
Open Access
A deep learning approach for identifying cancer survivors living with post-traumatic stress disorder on Twitter Nur Hafieza Ismail1* , Ninghao Liu1, Mengnan Du1, Zhe He2 and Xia Hu1 From The 4th International Workshop on Semantics-Powered Data Analytics Auckland, New Zealand. 27 October 2019
Abstract Background: Emotions after surviving cancer can be complicated. The survivors may have gained new strength to continue life, but some of them may begin to deal with complicated feelings and emotional stress due to trauma and fear of cancer recurrence. The widespread use of Twitter for socializing has been the alternative medium for data collection compared to traditional studies of mental health, which primarily depend on information taken from medical staff with their consent. These social media data, to a certain extent, reflect the users’ psychological state. However, Twitter also contains a mix of noisy and genuine tweets. The process of manually identifying genuine tweets is expensive and time-consuming. Methods: We stream the data using cancer as a keyword to filter the tweets with cancer-free and use post-traumatic stress disorder (PTSD) related keywords to reduce the time spent on the annotation task. Convolutional Neural Network (CNN) learns the representations of the input to identify cancer survivors with PTSD. Results: The results present that the proposed CNN can effectively identify cancer survivors with PTSD. The experiments on real-world datasets show that our model outperforms the baselines and correctly classifies the new tweets. Conclusions: PTSD is one of the severe anxiety disorders that could affect individuals who are exposed to traumatic events, including cancer. Cancer survivors are at risk of short-term or long-term effects on physical and psycho-social wellbeing. Therefore, the evaluation and treatment of PTSD are essential parts of cancer survivorship care. It will act as an alarming system by detecting the PTSD presence based on users’ postings on Twitter. Keywords: PTSD, Cancer survivor, Social media, Deep learning
Background PTSD is a psychological disorder that occurs in some people after witnessing or experiencing traumatic events [1]. People who have suffered from war, a severe accident, a natural disaster, a sexual assault, and medical trauma are potentially at risk of developing PTSD. Almost half of the cancer fighters are diagnosed with a psychiatric disorder, with the majority * Correspondence: [email protected] 1 Department of Computer Science & Engineering, Texas A&M University, College Station, TX, USA Full list of author information is available at the end of the article
of them having chronic depression [2]. Cancer diagnosis, treatments (chemotherapy and radiation), post-treatment care, and recovery could affect the patients’ psychological condition and cause anxiety or trauma. Unstable mental health among cancer survivors is hazardous because they are at high risk of self-destruction and may also harm others once they lose self-control of their b
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