System
The system addresses the challenge of identifying biases and misinformation in news articles by using AI to detect bias language, evaluate source reliability, and perform sentiment analysis, thereby enabling readers to make informed decisions and promoting media literacy.
JP2025054227APending Publication Date: 2025-04-07SOFTBANK GROUP CORP
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Patent Information
- Application Number
- JP2024163063
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2023-09-25
- Filing Date
- 2024-09-19
- Publication Date
- 2025-04-07
AI Technical Summary
Technical Problem
Conventional technologies face challenges in efficiently identifying biases and misinformation in news articles, making it difficult for readers to make informed decisions.
Method used
A system comprising a reception unit, detection unit, evaluation unit, analysis unit, and visualization unit that analyzes news articles using AI to detect bias language, evaluate source reliability, perform sentiment analysis, and visualize results, allowing readers to assess the reliability of information.
Benefits of technology
The system effectively identifies biases and misinformation in news articles, enabling readers to make informed decisions and promoting media literacy.
✦ Generated by Eureka AI based on patent content.
Abstract
To provide a system that specifies a bias or false information in a news article to allow a reader to calmly determine information.SOLUTION: A system according to an embodiment comprises a receiving unit, a detection unit, an evaluation unit, an analysis unit, and a visualization unit. The receiving unit inputs a text of a news article. The detection unit analyzes the text input by the receiving unit and detects a bias language. The evaluation unit evaluates the reliability of a source on the basis of the bias language detected by the detection unit. The analysis unit performs emotion analysis on the basis of a result of the evaluation performed by the evaluation unit. The visualization unit visualizes a result of the emotion analysis performed by the analysis unit.SELECTED DRAWING: Figure 1
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