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  ### Curation Rationale
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  The PHORECAST dataset aims to map real human profiles (demographics, personality, and locus of control) to their responses / reactions from interacting with various public health campaigns. The primary purpose is for academic research to study how different people interact with stimuli and simulate how and why different communities respond differently to visuals. The results will be used to build an AI simulator that can mimic real world communities.
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  ### Source Data
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  <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
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  All collection and processing stages were done using Python. More information can be found in the paper and on our github.
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  #### Who are the source data producers?
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  Correspondence to rqadri@umd.edu
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  ### Annotations [optional]
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  <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
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  The dataset is primarily in English, limiting global applicability of our method.
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- [More Information Needed]
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  ### Recommendations
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  <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
 
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  ### Curation Rationale
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  The PHORECAST dataset aims to map real human profiles (demographics, personality, and locus of control) to their responses / reactions from interacting with various public health campaigns. The primary purpose is for academic research to study how different people interact with stimuli and simulate how and why different communities respond differently to visuals. The results will be used to build an AI simulator that can mimic real world communities.
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  ### Source Data
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  <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
 
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  All collection and processing stages were done using Python. More information can be found in the paper and on our github.
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  #### Who are the source data producers?
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  Correspondence to rqadri@umd.edu
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  ### Annotations [optional]
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  <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
 
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  The dataset is primarily in English, limiting global applicability of our method.
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  ### Recommendations
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  <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->