| Summary: | Web scraping has numerous applications. It can be used complementary with APIs to extract
useful data from web pages. For instance, commercial data is abundant, but not always relevant as
it is presented on websites. In this paper, we propose the usage of web scraping techniques
(namely, two popular libraries – BeautifulSoup and Selenium) to extract data from web and other
Python libraries and techniques (vaderSentiment, SentimentIntensityAnalyzer, nltk, n consecutive
words) to analyze the reviews and obtain useful insights from this data. A web scraper is built in
which prices are extracted and variations are tracked. Furthermore, the reviews are extracted and
analyzed in order to identify the relevant opinions, including complaints of the customers.
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