Web Scraping as a scientific tool for theoretical reference

Abstract

The use of Web Scraping via Python reveals significant potential for its utilization as a scientific tool for data acquisition, playing a crucial role in constructing the theoretical framework in scientific writing. This study encompasses both the theoretical and practical aspects of the data acquisition process. Initially, the importance of ethics in online data collection is emphasized, respecting the terms of use and privacy regulations established by Nature. Web scraping is explored as an effective technique, supported by the Beautiful Soup and Requests libraries, which automate data extraction responsibly. The application of the Tkinter library for creating user-friendly graphical interfaces is discussed, allowing for more accessible interaction for all users. The relevance of the DataFrame as a structure for handling and analyzing tabular data is also highlighted, along with the strategic choice to save data in Excel format, enhancing accessibility and collaboration, courtesy of the Pandas library. Combined, these elements form a cohesive and ethical approach to web data acquisition and analysis, in harmony with the theoretical framework in scientific writing.