This document discusses a research project on detecting fake news. It introduces the team members working on the project and explains that the goal is to address the negative impacts of widespread fake news spread on social media. The research methodology will use techniques like naïve bayes classifier and random forest to analyze qualitative and quantitative data and identify patterns that distinguish fake from factual news. The system is still being developed and tested using various datasets including social media, search engines, and fact-checking websites. The conclusion is that this fake news detection system aims to curb the spread of misinformation online by classifying new stories as true or fake.

2. Fake news detection

3. Team Members
Name: Harun-or-
Rashid
ID:193-15-2966
Name: Robiul Islam
Apon
ID:193-15-2994
Name: Sanad
Bhowmik
ID:193-15-2952

4. What is the research about?
 Social media for news consumption is a double-edged sword.
 It’s low cost.
 Easy access.
 Rapid dissemination of information lead people to seek out and
consume news from social media.
 The extensive spread of fake news has the potential for extremely
negative impacts on individuals and society.

5. Purpose
 The tremendous growth and impact of pretend news .
 A hot research field gained the public’s attention and
threatened their safety.
 A good range of developed fashions to detect fake contents.
 It utilizes qualitative and quantitative data analysis as an
analytic method to spot systematic nuances between fake and
factual news.

6. Research Methodology
Naïve Bayes
Classifier Random Forest
Logistic regression

7. Dataset
 Social media websites.
 Search engine.
 Fact-checking websites.
 Buzzfeed News.
 BS Detector.

8. Result
Working…

9. Conclusion
 Newspapers that were earlier preferred as hardcopies are now being substituted by applications like Facebook, Twitter, and
news articles to be read online
 Its makes things more complicated and tries to change the opinion and attitude of people towards use of digital technology.
 In order to curb the phenomenon, we have developed our Fake news Detection system that takes input from the user and
classify it to be true or fake.

10. Any Questions ?