Mortality Classification

User-generated content is central to social computing scholarship. However, researchers and practitioners often presume that these users are alive. Failing to account for mortality is problematic in social media where an increasing number of profiles represent those who have died. Identifying mortality can empower designers to better manage content and support the bereaved, as well as promote high-quality data science. Based on a computational linguistic analysis of post-mortem social media profiles and content, we report on classifiers developed to detect mortality and show that mortality can be determined after the first few occurrences of post-mortem content. Applying our classifiers to content from two other platforms also provided good results. Finally, we discuss trade-offs between models that emphasize pre- vs. post-mortem precision in this sensitive context. These results mark a first step toward identifying mortality at scale, and show how designers and scientists can attend to mortality in their work.

Publications

Tending Unmarked Graves: Classification of Post-mortem Content on Social Media Jiang, Jialun "Aaron" and Brubaker, Jed R.
Proc. ACM Hum.-Comput. Interact. 2, CSCW: Article 81
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- DOI: 10.1145/3274350
User-generated content is central to social computing scholarship. However, researchers and practitioners often presume that these users are alive. Failing to account for mortality is problematic in social media where an increasing number of profiles represent those who have died. Identifying mortality can empower designers to better manage content and support the bereaved, as well as promote high-quality data science. Based on a computational linguistic analysis of post-mortem social media profiles and content, we report on classifiers developed to detect mortality and show that mortality can be determined after the first few occurrences of post-mortem content. Applying our classifiers to content from two other platforms also provided good results. Finally, we discuss trade-offs between models that emphasize pre- vs. post-mortem precision in this sensitive context. These results mark a first step toward identifying mortality at scale, and show how designers and scientists can attend to mortality in their work.
Describing and Classifying Post-Mortem Content on Social Media Jiang, Jialun "Aaron" and Brubaker, Jed
Proceedings of the Twelfth International Conference on Web and Social Media (ICWSM-2018)
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As the quantity of user profiles on social media grows, so does the number of post-mortem profiles. In this paper, we present a computational linguistic analysis of post-mortem social media profiles. Specifically, we provide an analysis of pre- vs. post-mortem language use, followed by a description of classifiers we developed that can accurately classify the mortality of social media profiles. These results shed initial lights into the ways in which people speak to the dead, and mark a first step toward accurately identifying mortality on a large scale.

Blog

Tending Unmarked Graves: Automatic Identification of Post-mortem Content on Social Media