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  "Package": "validateIt",
  "Title": "Validating Topic Coherence and Topic Labels",
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  "Description": "By creating crowd-sourcing tasks that can be easily posted\nand results retrieved using Amazon's Mechanical Turk (MTurk)\nAPI, researchers can use this solution to validate the quality\nof topics obtained from unsupervised or semi-supervised\nlearning methods, and the relevance of topic labels assigned.\nThis helps ensure that the topic modeling results are accurate\nand useful for research purposes. See Ying and others (2022)\n<doi:10.1101/2023.05.02.538599>. For more information, please\nvisit\n<https://github.com/Triads-Developer/Topic_Model_Validation>.",
  "License": "GPL (>= 2)",
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  "Author": "Luwei Ying [aut, cre]\n(<https://orcid.org/0000-0001-7307-4834>), Jacob Montgomery\n[aut], Brandon Stewart [aut]",
  "Maintainer": "Luwei Ying <triads.developers@wustl.edu>",
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  "Date/Publication": "2023-05-16 07:20:02 UTC",
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    "author": "Luwei Ying <triads.developers@wustl.edu>",
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      "page": "validateLabel",
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