dynamic detection of data truthfulness with vulgarity removal and social media analysis using big datas
Sundhari M,Aravindhan.K,Mano S,Silambarasan.M
Published in International Journal of Advanced Research in Computer Science Engineering and Information Technology
ISSN: 2321-3337 Impact Factor:1.521 Volume:6 Issue:3 Year: 22 April,2024 Pages:1907-1911
Abstract
Social media's surge in popularity made it possible to gather a lot of organically occurring data on people's conversations with one another. Social media conversations can frequently yield a number of characteristics, including the text content, the sender and recipient, the date and time, and the locations of the sender and recipient. The wealth of data enables researchers to look at human behaviour from a variety of angles. However, when evaluating the components of human behaviour, the majority of research simply look at one dimension. As everyone knows, there are a lot of rumours on social media, and the information is also unreliable. Based on user input, we are eliminating rumours from posts on our prototype social media. We also exclude vulgar phrases from data posts on our prototype social media. We also examine the content that the public posts on social media that expresses their dissatisfaction, frustration, and protests. In order to effectively analyze data, we use big data to filter the content and compare it with the specified keywords. Together with the obscene keywords, we define the collection of protesting keywords. User inputs are sent to big data for efficient filtering and comparison. Our project will delete the post from our prototype social media if the terms match the trained keywords. Our social media prototype was created with a Java user interface and a MySQL backend database. For the purpose of filtering, the server stores each taught term.
Kewords
Vulgar phrases, big data, Filtering
Reference
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