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scraping-tweets-from-twitter-using-twitter-api-tweepy- icon scraping-tweets-from-twitter-using-twitter-api-tweepy-

Downloaded all the tweets corresponding to the Page name specified.Applied date range filter to scrap specific tweets which where tweeted in between the specified data range. The obtained results were then saved in an excel / csv file.

scrapping-google-images-using-selenium. icon scrapping-google-images-using-selenium.

Did a Google search of any keyword for which need to download images. The keyword related Google Images will obtained.Then, specified the count of image which need to be downloaded. The program downloaded only that particular number of images, as per the specified count. If 100 count is specified, then program will download no more than 100 images.

scrapping-instagram-page-content-using-selenium. icon scrapping-instagram-page-content-using-selenium.

Search for any particular page using a search box on Instagram. Select the desired Instagram page. Download the following data for each post posted by that page: • Post Caption • No of Post Likes • All the comments corresponding to a post. These obtained data were then stored in excel / csv file.

trendogate-scraping-code. icon trendogate-scraping-code.

I used TrendoGate website which has the archived data regarding the trending Twitter hashtags. On this website, I applied the country and date filter to narrow down my search. For ex – country as ‘India’ and date as ‘1/1/2019 to till today’.The obtained results were nothing but the trending hashtags for that particular day. Upon clicking on each hashtag, we are redirected to a page which shows all the tweets which has that hashtag used in it. So likewise, I fetched all the tweets which are linked to all those hashtags which were trending on that particular day.

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