A Web Scraper For Forums : Navigation and text extraction methods

Abstract: Web forums are a popular way of exchanging information and discussing various topics. These websites usually have a special structure, divided into boards, threads and posts. Although the structure might be consistent across forums, the layout of each forum is different. The way a web forum presents the user posts is also very different from how a news website presents a single piece of information. All of this makes the navigation and extraction of text a hard task for web scrapers. The focus of this thesis is the development of a web scraper specialized in forums. Three different methods for text extraction are implemented and tested before choosing the most appropriate method for the task. The methods are Word Count, Text-Detection Framework and Text-to-Tag Ratio. The handling of link duplicates is also considered and solved by implementing a multi-layer bloom filter. The thesis is conducted applying a qualitative methodology. The results indicate that the Text-to-Tag Ratio has the best overall performance and gives the most desirable result in web forums. Thus, this was the selected methods to keep on the final version of the web scraper.