Project Presentation: News Aggregator with Sympathy Control Introduction
Purpose: Develop a news aggregator capable of gathering news articles from various sources and conducting a sympathy control to display the text's bias and sympathy.
Background: With the increasing amount of information online, it's crucial for users to access news in an objective manner and be aware of any biases in news reporting.
Goal: Create a platform that provides users with access to a variety of news perspectives while making them aware of potential biases.
System Architecture
Data Collection:
Utilization of web scraping to gather news articles from different sources and news websites.
Sympathy Control:
Employing natural language processing (NLP) and machine learning to analyze the texts of news articles.
Developing algorithms to measure bias and sympathy in the text based on keywords, tone, and other contextual information.
User Interface:
Designing a user-friendly web application where users can search for news and view sympathy control results.
Sympathy Control Methodology
Text Analysis:
Identification of keywords and phrases that may indicate bias or sympathy in the text.
Analysis of tone and linguistic style to assess the news article's objectivity.
Machine Learning:
Training machine learning models using labeled datasets to automatically classify news articles according to their sympathy and bias.
Continuous improvement of the models through feedback loops from user interactions.
User Experience
Search and Filtering:
Allow users to search for news based on various criteria such as topic, source, and date.
Implement filtering options to display news with different levels of sympathy and bias.
Visualization of Results:
Present sympathy control results in a clear and user-friendly manner, perhaps through color-coding or graphical diagrams.
Offer users the ability to obtain more detailed information on why a news article is assessed in a certain way.
Technical Challenges
Web Scraping and Data Quality: Manage variations in data formats and ensure high quality of collected news articles.
NLP and Bias Analysis: Develop accurate algorithms to properly measure bias and sympathy in news texts, despite linguistic nuances and contextual complexity.
User Interface Design: Create an intuitive and responsive web application that offers a good user experience and clear communication of sympathy control results.
Conclusions and Future Work
Conclusions: Presentation of the project's progress and achieved results compared to the original goals.
Future Work: Identification of potential areas for improvement and new features to further enhance the news aggregator and sympathy control.