This web platform is designed for analyzing the cryptocurrency popularity in media using information from news websites. The characteristic features of Hypeanalysis are data mining with spiders written in Python and visual representation of analysis results in form of charts.
2 Spider Types
were used to scrape data from websites.
written for different source websites.
Hypeanalysis is a complex fintech project that combined data mining, analysis and other functionalities. Its core represents a web platform for data collection, processing and visualization to provide statistics on popularity of different cryptocurrencies. The results of the analysis are based on source data scraped from various news websites and are visualized in form of informative and convenient charts. The processed data provides valuable business information for platform users.
Hypeanalysis wasn’t much of a challenge, since we had already completed similar but far more complex projects, such as Mememachine. All functional components were realized with the help of best suitable technologies, primarily Python and React.js. In addition to the data mining functionality realized by scraping spiders written for particular websites, we implemented measurement of ICO mentions in media, stylized visual representation, as well as Hypeindex calculation and cryptocurrency popularity comparison both based on mentions. This web platform also included other requested and proposed features for the purposes of business intelligence to fully meet the customer’s requirements.
The outcome of our work over the Hypeanalysis project was a solid software solution to our portfolio and another satisfied customer to our business reputation. The efficient communication with the client was a little tricky due to his specific vision of the concept. However, we defined specifications, set goals and priorities, coordinated the schedule, and delivered the final product in time. Overall, this project was a good practice to advance our team experience and cooperation skills.