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IJIRTM: Volume-6, Issue-6, 2022

Paper Title : A Review on Recent Trends of Fake News Detection on Social Media
Author Name : Nikita Katakwar, Prof.Chetan Agrawal, Prof.Pawan Meena
Keywords : Fake news detection, machine learning, deep learning, social media, ensemble techniques, N-gram analysis.
Abstract :

In the past decade, the social networks platforms and micro-blogging sites such as Facebook, Twitter, Instagram and Sina Weibo have become an integral part of our day-to-day activities and is widely used all over the world by billions of users to share their views and circulate information in the form of messages, pictures, and videos. These are even used by government agencies to spread important information through their verified Facebook accounts and official Twitter handles, as it can reach a huge population within a limited time window. However, many deceptive activities like propaganda and rumor can mislead users on a daily basis. In this COVID times the fake news and rumors are very prevalent and are shared in a huge number which has created chaos in this tough time. And hence, the need of Fake News Detection it the present scenario is inevitable. In this paper, we survey the recent literature about different approaches to detect fake news over the Internet. In particular, we firstly discuss about fake news and the various terms related to it that have been considered in the literature. Secondly, we highlight the various publicly available datasets and various online tools that are available and cam debunk Fake News in real time. Thirdly, we describe fake news detection methods based on two broader areas i.e., it’s content and the social context. Finally, we provide a comparison of various techniques that are used to debunk fake news.

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Paper Title : Movie Reviews Prediction Using Machine Learning Techniques: A Survey
Author Name : Ashwini Meshram, Prof.Chetan Agrawal, Prof.Prachi Tiwari
Keywords : Sentiment Analysis, Movie Review, Machine Learning, Deep Learning, SVM KNN.
Abstract :

In recent years, the predictive model has seen an increase in volume thanks to the application of machine learning. The film business is still quite significant, as seen by the hundreds of new films that are produced each year. The likelihood of a film's commercial success can be influenced by a wide range of elements, including film critics, actors, directors, actresses, and composers, amongst others. Several writers have proposed or implemented several approaches and algorithms for forecasting the success of movies, including KNN, SVM, Naive Bayes Classifier, Logistic regression, random forest, and others. These approaches and techniques include: In this study, we give a literature review on the topic of predicting the Reviews of a movie by employing a variety of machine learning algorithms. We also make some recommendations for further research.

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Paper Title : Machine Learning Based Efficient Prediction of Human Heart Disease by Identifying the Features
Author Name : Deepak Kumar Rathore, Dr.Sunil Phulre
Keywords : Information and Communication Technology, Artificial Intelligence, Machine Learning, Health Care.
Abstract :

Hospitals and clinics are constrained to storing and analyzing medical data using traditional and manual methods. Many medical institutions have made significant efforts to overcome this limitation by combining considerable data resources with new technologies, there is still a lack of knowledge about diseases and how to treat them, despite the enormous number of data available. Machine learning and data-driven tactics can produce accurate diagnostic tools. The current study aims to identify and predict the heart disease at an early stage and saves the human life. In this paper, we used the machine learning based performance result evaluation and find the better prediction ratio for the heart disease.

Download IJIRTM-6-6-0606202203
Paper Title : Performance Evaluation of Reactive Mobile Ad-hoc Network Routing Protocols
Author Name : Amrita Singh, Prof.Mahendra Singh Sisodia, Prof.Pankaj Pandey
Keywords : Mobile ad-hoc Network, Network simulator, Throughput, Packet delivery ratio.
Abstract :

The mobile ad-hoc networks is considered a group of wireless mobile nodes that are capable of communicating with each other without the use of network infrastructure or any centralized administration. A MANET have a large number of potential applications like tactical networks, emergency services, commercial and civilian environments, home and enterprise networking, education, entertainment, sensor networks, context aware servicing and coverage extension. In this paper, our proposed modified scheme “EA-DSR” simulate in network simulator 2.34. In simulation process we used 10, 20, 30 and 50 nodes. The evaluation of performance is measured by packet delivery ratio, End to end delay and packet throughput. Our proposed scheme EADSR gives good results in compare with existing DSR method.

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