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Time series on search queries are collected and analyzed via Google Trends, for three of the most common trending topics. For Analytics, we have chosen some of the hot topics, Tourism, Unemployment, and Advertisement. For Analyzing, we have chosen R for making our tool to deploy data analytics. The data could take from anywhere so we have taken data and downloaded our datasets for United States Where all these attributes inflation and deflation can be shown in large numbers. The Second step is to create an application in R , Which involves various libraries and functions such like libraries shinythemes, dplyr, readr and functions like functionsreadcsv, Control Panel Slider , slider Panel etc. We need to simply design a Gui form application which will read the data from the csv files and then process the numbers in it to plot a graph (renderplot()) within a time stamp given. The time stamp is allowed to be chosen between 2007 and 2017, which will create a huge data and will give a large data analysis. Even we have implemented a smoother for smoothing the trends between times (date range). KeywordsGoogle trends, Analysis, Data Analytics, Tourism, Unemployment, Advertisement, Application, Implement

Trend Analysis: Unemployment, Tourism and Advertisement