Data Scraping into Spreadsheets

Gemfeed is a recommendation's platform where influencers from all around the globe post the books, movies or TV shows they like. Currently, we have more than 800 influencers on the website and the amount is growing each week. In Gemfeed, you can find a large collection of books,movies or TV shows to add to your wishlist (and watch them whenever you want!) while share your opinions with other users about the latest books, movies or TV shows launched. The work consists of Scraping information sources through '[login to view URL]'(see image 'Ex2' or through the browser's console, for 'csv' files. Information sources are newspaper/magazine articles or web articles where 'influencers' appear recommending books, movies and/or tv shows. From these sources, five different categories must be obtained: Name of the 'influencer', Avatar of the 'influencer', Title of the recommendations made, comments on its recommendations and source (URL). Either through '[login to view URL]' or browser's console, the person must create an Excel sheet([login to view URL] generates the Excel sheet itself) that contains the following columns: user_ name user_avatar item_title type (book / video) description source We provide the sources, they don't need to be found by the 'freelancer'. Sometimes 'user_avatar' or 'description' won't appear on the source. It is impertant to include an avatar so it can be searched through google (filtered by size: Large). The type refers to the recommendation of the 'influecer' (use 'book' to books and 'video' to films and TV movies). This column is inserted manually, you don't have to obtain it from the web source. The description is not mandatory if the source does not provide it. You are asked to create a row of Excel for each referral(see the image attached 'Ex1' for more informartion. Finally, these Excel files are converted into '.csv' that will be sent to our email so that from there, we create new profiles on the web. Our intention is to build a long term relationship with the person we hire, helping us finding more content to upload to the platform each week.