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Fake News Detection Using Data Mining Techniques

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dc.contributor.author Hasan, MD: Mehedi
dc.contributor.author Harun-Or-Rashid, MD:
dc.date.accessioned 2020-10-10T06:50:03Z
dc.date.available 2020-10-10T06:50:03Z
dc.date.issued 2019-12-10
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/4640
dc.description Communication plays a vital role in moving the modern world forward. Now this communication system has become much easier. Now almost all of us are leaning on the news online. But sadly, the fact is, many news portals are now spreading fake news. Again some people have been relying on these fake news stories. This has led to many adverse effects in various sectors of society. Political sports business entertainment is also having an adverse effect in many sectors for all these fake news, and people are facing harassment in various ways. Which is never good for us. Now is the time to detect fake news by showing the proportion of wrong news among people. Every minute, many news posts are published from various news protocols on the revolutionary web of the world, say CNN, BBC, BuzzFeed, Daily star, PolitiFact, etc. [1]. The main intention of this paper is to automatically detect the fake news talk. We collect some datasheets from real-life and make the news content relevant to the news through knowledge-based context and style best method and by identifying and analyzing it. Based on the features of this fake news we develop an accuracy set, in the end, our accuracy rate stands at 82% . en_US
dc.description.abstract Social Media is becoming the most popular web site to seek news day by day because of the easy access facility worldwide. It’s very cost-effective and people can easily collect news & entertainment from any corner of the world with just a simple click. It’s helping the world to be open on the other hand it’s true that a rumor can make disaster within a minute which is very easy to spread by such open media. The availability of low-quality news and false information can mislead the readers & which is done intentionally by a group of people. In this century of digital society, fake news & rumor are the biggest threats because it can easily bring several negative impacts on society. It’s very much challenging for readers to differentiate between fake news and real news. Some of the online news portal, blogs & sites who have no proper authorization to publish news but they are continually publishing different types of rumors or worthless news but with spicy headlines to seek the attention of readers which made it challenging to identify reliable and authorized news sources. They intend to spread rumor & earn revenue by making advertisements on their sites. This could make sufferers a large number of peoples at a time. In this paper, we focus on the automatic identification of fake news by using a novel algorithm that’s “decision tree algorithm”. We may not stop fake news from being made but we can limit to share it. To make limitations on any site, we need assistance from the concerned department of a state or government. Our target is to select headlines of news & send them to the algorithm as well as stop the spread of news which is identified as fake news by the decision tree algorithm. To be successful, we need the help of the central information cell of a country. Our vision is to stop the deceptive information & rumor by limiting the propagation of fake news in social media as well as web sites. It is very challenging but our novel algorithm will perform well to detect fake news and able to get high accuracy over time. en_US
dc.language.iso en en_US
dc.publisher Daffodil International University en_US
dc.subject Data Mining en_US
dc.subject Technology en_US
dc.subject Bad News en_US
dc.title Fake News Detection Using Data Mining Techniques en_US
dc.type Other en_US

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