Data_Dredge detects the unreal truth around you .!
Why? Because To aware of real world.
Overview • Problem Statement • Installation • Screenshots • Demo • Presentation • Report a bug
The problem of detecting false news on social media has recently received a lot of attention. The fundamental countermeasure of evaluating websites against a list of labelled false news sources is rigid, thus a machine learning technique is preferable. Our study attempts to employ machine learning algorithms to detect false news based on the text content of news items.
Create a machine learning software that can detect when a news site is spreading false news. We want to create a classifier that can make judgements about information based on a corpus of labelled actual and fraudulent news stories. Based on many articles emanating from a source, the algorithm will concentrate on identifying fake news sources. We can anticipate with high confidence that any future publications from a source classified as a producer of false news will likewise be fake news. Because we will have several data points from each source, focusing on sources increases our article misclassification tolerance.
The project's planned application is to be used in applying visibility weights in social media. Using the weights generated by this approach, social networks can reduce the visibility of stories that are extremely likely to be fake news.
Planning: -
- Data Collection
- Model Building
- Backend work
- Deployment
Use the package manager pip to install library.
pip install virtualenvvirtualenv env_nameenv_name/scripts/activateFollow these commands to start your project.
pip install -r requirements.txtpython app.py
