Fighting Fake News and Identifying Trends
📌 Introduction In the modern information age, the rapid dissemination of news has led to the spread of fake news becoming a significant concern. Our project aims to combat this by identifying and mitigating the spread of fake news using big data technologies.
🚀 Highlights Fake News Concern: Fake news, or misleading information presented as factual, can manipulate public opinion and erode trust in traditional news sources. Power of Big Data: Harness the vast datasets, like social media posts, news articles, and user-generated content, to uncover hidden patterns and insights. GDELT Project: Utilize the GDELT project, a massive repository of global news data, to collect real-time news articles and gain diverse news sources insights. Machine Learning: Apply machine learning techniques to the news articles dataset to detect patterns distinguishing authentic news from potentially fake news. User Interface: Provide a user-friendly dashboard for accessing verified authentic trending news worldwide.
💡 Objective Detect and combat the spread of fake news and identify global news trends using big data technologies and machine learning.
🛠️ Technologies Used GDELT Analysis Service API Big Data Processing Tools (Please specify the tools you've used, e.g., Apache Spark, Hadoop, etc.) Machine Learning Libraries (Specify the libraries, e.g., TensorFlow, scikit-learn, etc.)
📊 Dataset We leverage the GDELT project as a primary data source, collecting real-time news articles to access a diverse range of news sources globally.