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- W3098491645 abstract "Background: Studies examining how sentiment on social media varies depending on timing and location appear to produce inconsistent results, making it hard to design systems that use sentiment to detect localized events for public health applications." @default.
- W3098491645 created "2020-11-23" @default.
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- W3098491645 date "2019-05-08" @default.
- W3098491645 modified "2023-10-02" @default.
- W3098491645 title "Modeling Spatiotemporal Factors Associated With Sentiment on Twitter: Synthesis and Suggestions for Improving the Identification of Localized Deviations" @default.
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- W3098491645 doi "https://doi.org/10.2196/12881" @default.
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