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- W2277302289 abstract "Several projects have shown the feasibility to use emph{textual} social media data to track public health concerns, such as temporal influenza patterns or geographical obesity patterns. In this paper, we look at whether geo-tagged emph{images} from Instagram also provide a viable data source. Especially for lifestyle diseases, such as obesity, drinking or smoking, images of social gatherings could provide information that is not necessarily shared in, say, tweets. In this study, we explore whether (i) tags provided by the users and (ii) annotations obtained via automatic image tagging are indeed valuable for studying public health. We find that both user-provided and machine-generated tags provide information that can be used to infer a county's health statistics. Whereas for most statistics user-provided tags are better features, for predicting excessive drinking machine-generated tags such as liquid' and glass' yield better models. This hints at the potential of using machine-generated tags to study substance abuse." @default.
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- W2277302289 date "2016-05-07" @default.
- W2277302289 modified "2023-10-17" @default.
- W2277302289 title "Social Media Image Analysis for Public Health" @default.
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- W2277302289 doi "https://doi.org/10.1145/2858036.2858234" @default.
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