A Combined Approach of Web Content Mining and Neural Networks for Predicting the societal impact of covid-19 through twitter

Abstract

Web data mining became an easy and important platform for retrieval of useful information. Users prefer World Wide Web more to upload and download data. As increasing growth of data over the internet, it is getting difficult and time consuming for discovering informative knowledge and patterns. Digging knowledgeable and user queried information from unstructured and inconsistent data over the web is not an easy task to perform. Different mining techniques are used to fetch relevant information from web (hyperlinks, contents, web usage logs). Web data mining is a sub discipline of data mining which mainly deals with web. Web data mining is divided into three different types: web structure, web content and web usage mining. Page content mining also called web scrapping is the technique under web mining that is used for extracting the web data. It is used in combination with the deep neural network algorithm to generate a combined data set. This paper mainly focuses on web content mining technique for the generation of covid-19 twitter data set.