METZLER H, BAGINSKI H, NIEDERKROTENTHALER T und GARCIA D, 2022. Detecting Potentially Harmful and Protective Suicide-Related Content on Twitter: Machine Learning Approach. Journal of medical Internet research. 17 August 2022. Vol. 24, no. 8, p. e34705-e34705. DOI 10.2196/34705.
Elsevier - Harvard (with titles)Metzler H, Baginski H, Niederkrotenthaler T, Garcia D, 2022. Detecting Potentially Harmful and Protective Suicide-Related Content on Twitter: Machine Learning Approach. Journal of medical Internet research 24, e34705-e34705. https://doi.org/10.2196/34705
American Psychological Association 7th editionMetzler H, Baginski H, Niederkrotenthaler T, & Garcia D. (2022). Detecting Potentially Harmful and Protective Suicide-Related Content on Twitter: Machine Learning Approach. Journal of Medical Internet Research, 24(8), e34705-e34705. https://doi.org/10.2196/34705
Springer - Basic (author-date)Metzler H, Baginski H, Niederkrotenthaler T, Garcia D (2022) Detecting Potentially Harmful and Protective Suicide-Related Content on Twitter: Machine Learning Approach.. Journal of medical Internet research 24:e34705-e34705. https://doi.org/10.2196/34705
Juristische Zitierweise (Stüber) (Deutsch)Metzler H/ Baginski H/ Niederkrotenthaler T/ Garcia D, Detecting Potentially Harmful and Protective Suicide-Related Content on Twitter: Machine Learning Approach., Journal of medical Internet research 2022, e34705-e34705.