YoutubeCommentsRankingYouTubeCommentTextQualityAnnotation

AI Overview😉

  • The potential purpose of this module is to evaluate the quality of YouTube comments and identify those that are potentially harmful or low-quality. This is done by using a machine learning model to predict the likelihood of a user flagging a comment as inappropriate.
  • This module could impact search results by influencing the ranking of YouTube videos based on the quality of their comments. Videos with high-quality comments may be ranked higher, while those with low-quality comments may be demoted. This could also affect the visibility of videos with toxic or offensive comments.
  • To be more favorable for this function, a website may focus on creating a positive and respectful community by encouraging users to engage in high-quality discussions, moderating comments to remove toxic or offensive content, and implementing mechanisms to report and flag inappropriate comments. This could also involve using natural language processing techniques to analyze and improve the quality of comments on their platform.

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GoogleApi.ContentWarehouse.V1.Model.YoutubeCommentsRankingYouTubeCommentTextQualityAnnotation (google_api_content_warehouse v0.4.0)

Text quality scores for a single comment.

Attributes

  • flagPredictionScore (type: number(), default: nil) - Score produced by the user flag prediction model.
  • flagPredictionVersion (type: String.t, default: nil) - Version identifier of the flag prediction model.

Summary

Types

t()

Functions

decode(value, options)

Unwrap a decoded JSON object into its complex fields.

Types

Link to this type

t()

@type t() ::
  %GoogleApi.ContentWarehouse.V1.Model.YoutubeCommentsRankingYouTubeCommentTextQualityAnnotation{
    flagPredictionScore: number() | nil,
    flagPredictionVersion: String.t() | nil
  }

Functions

Link to this function

decode(value, options)

@spec decode(struct(), keyword()) :: struct()

Unwrap a decoded JSON object into its complex fields.