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Predicting suicide risk from online postings in Reddit : the UGent-IDLab submission to the CLPysch 2019 Shared Task A

Semere Kiros Bitew (UGent) , Ioannis Bekoulis (UGent) , Johannes Deleu (UGent) , Lucas Sterckx (UGent) , Klim Zaporojets (UGent) , Thomas Demeester (UGent) and Chris Develder (UGent)
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Abstract
This paper describes IDLab’s text classification systems submitted to Task A as part of the CLPsych 2019 shared task. The aim of this shared task was to develop automated systems that predict the degree of suicide risk of people based on their posts on Reddit. Bag-of-words features, emotion features and post level predictions are used to derive user-level predictions. Linear models and ensembles of these models are used to predict final scores. We find that predicting fine-grained risk levels is much more difficult than flagging potentially at-risk users. Furthermore, we do not find clear added value from building richer ensembles compared to simple baselines, given the available training data and the nature of the prediction task.

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MLA
Bitew, Semere Kiros, et al. “Predicting Suicide Risk from Online Postings in Reddit : The UGent-IDLab Submission to the CLPysch 2019 Shared Task A.” Computationallinguistics and Clinical Psychology : From Keyboard to Clinic : Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology, Association for Computational Linguistics (ACL), 2019, pp. 158–61.
APA
Bitew, S. K., Bekoulis, I., Deleu, J., Sterckx, L., Zaporojets, K., Demeester, T., & Develder, C. (2019). Predicting suicide risk from online postings in Reddit : the UGent-IDLab submission to the CLPysch 2019 Shared Task A. In Computationallinguistics and clinical psychology : from keyboard to clinic : Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology (pp. 158–161). Minneapolis, USA: Association for Computational Linguistics (ACL).
Chicago author-date
Bitew, Semere Kiros, Ioannis Bekoulis, Johannes Deleu, Lucas Sterckx, Klim Zaporojets, Thomas Demeester, and Chris Develder. 2019. “Predicting Suicide Risk from Online Postings in Reddit : The UGent-IDLab Submission to the CLPysch 2019 Shared Task A.” In Computationallinguistics and Clinical Psychology : From Keyboard to Clinic : Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology, 158–61. Association for Computational Linguistics (ACL).
Chicago author-date (all authors)
Bitew, Semere Kiros, Ioannis Bekoulis, Johannes Deleu, Lucas Sterckx, Klim Zaporojets, Thomas Demeester, and Chris Develder. 2019. “Predicting Suicide Risk from Online Postings in Reddit : The UGent-IDLab Submission to the CLPysch 2019 Shared Task A.” In Computationallinguistics and Clinical Psychology : From Keyboard to Clinic : Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology, 158–161. Association for Computational Linguistics (ACL).
Vancouver
1.
Bitew SK, Bekoulis I, Deleu J, Sterckx L, Zaporojets K, Demeester T, et al. Predicting suicide risk from online postings in Reddit : the UGent-IDLab submission to the CLPysch 2019 Shared Task A. In: Computationallinguistics and clinical psychology : from keyboard to clinic : Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology. Association for Computational Linguistics (ACL); 2019. p. 158–61.
IEEE
[1]
S. K. Bitew et al., “Predicting suicide risk from online postings in Reddit : the UGent-IDLab submission to the CLPysch 2019 Shared Task A,” in Computationallinguistics and clinical psychology : from keyboard to clinic : Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology, Minneapolis, USA, 2019, pp. 158–161.
@inproceedings{8621471,
  abstract     = {This paper describes IDLab’s text classification systems submitted to Task A as part of the CLPsych 2019 shared task. The aim of this shared task was to develop automated systems that predict the degree of suicide risk of people based on their posts on Reddit. Bag-of-words features, emotion features and post level predictions are used to derive user-level predictions. Linear models and ensembles of these models are used to predict final scores. We find that predicting fine-grained risk levels is much more difficult than flagging potentially at-risk users. Furthermore, we do not find clear added value from building richer ensembles compared to simple baselines, given the available training data and the nature of the prediction task.},
  author       = {Bitew, Semere Kiros and Bekoulis, Ioannis and Deleu, Johannes and Sterckx, Lucas and Zaporojets, Klim and Demeester, Thomas and Develder, Chris},
  booktitle    = {Computationallinguistics and clinical psychology : from keyboard to clinic : Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology},
  isbn         = {9781948087957},
  language     = {eng},
  location     = {Minneapolis, USA},
  pages        = {158--161},
  publisher    = {Association for Computational Linguistics (ACL)},
  title        = {Predicting suicide risk from online postings in Reddit : the UGent-IDLab submission to the CLPysch 2019 Shared Task A},
  url          = {http://dx.doi.org/10.18653/v1/W19-3019},
  year         = {2019},
}

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