Machine Classification and Analysis of Suicide-Related Communication on Twitter-Reference-Cited by-同舟云学术

Machine Classification and Analysis of Suicide-Related Communication on Twitter

Published:2015 Issue: Volume: Page:
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Container-title:Proceedings of the 26th ACM Conference on Hypertext & Social Media - HT '15
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Author:

Burnap Pete,Colombo Walter,Scourfield Jonathan

Funder

Department of Health

Publisher

ACM Press

Reference39 articles.

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2. D. Baker and S. Fortune. Understanding self-harm and suicide websites. Crisis: The Journal of Crisis Intervention and Suicide Prevention, 29(3):118--122, 2008.

3. L. Barbosa and J. Feng. Robust sentiment detection on twitter from biased and noisy data. In Proceedings of the 23rd International Conference on Computational Linguistics: Posters, pages 36--44. Association for Computational Linguistics, 2010.

4. K. Becker and M. H. Schmidt. When kids seek help on-line: Internet chat rooms and suicide. reclaiming children and youth, 13(4):229--230, 2005.

5. L. Biddle, J. Donovan, K. Hawton, N. Kapur, and D. Gunnell. Suicide and the internet. Bmj, 336(7648):800--802, 2008.

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