With the rapid growth of the Internet, the amount of information in the digital environment has also increased. This increase has created the need for new techniques for organizing, accessing and analyzing information. "Crawlers" (web crawlers or web surfers), which are automated software that collect information by systematically scanning web pages, have become one of the main tools in this context. Crawlers are software systems designed to discover, index and analyze content on the web.

Definition and Basic Functions

Crawler (or web crawler) is software that automatically visits websites and crawls their content. One of the most common uses is in the indexing process of search engines. Through crawlers, a search engine visits websites, collects content and then organizes this data in a database to provide fast and relevant answers to user queries. Crawlers not only follow links, but also analyze page content, build hierarchies between links, and prioritize by content type.

Working Principle and Architecture

A web crawler usually starts with a list of URLs (to-do list). This list is called a "seed URL". The crawler visits the URLs in this list in turn, analyzes the page content and identifies new links on the page and adds them to its task list. This iterative process continues until a certain stopping criterion (e.g. depth limit, bandwidth limit or time limit).

Crawler architecture usually consists of the following basic components:

• Fetcher: Downloads the content from the URL via the HTTP protocol.
• Parser: Analyzes the content of the downloaded page, extracts text and detects new links.
• Scheduler: Determines which URL to crawl and when.
• URL Frontier: A data structure where new links collected during crawling are stored and sorted.
• Politeness Manager: Provides server-friendly behavior by preventing back-to-back requests to the same site.

Crawler Types

Web crawlers vary according to different purposes and architectures. The most common types of crawlers are:

• Focused Crawler: Prioritizes pages related to a specific topic or keyword.
• Distributed Crawler: Systems that run in parallel on multiple machines and are used for large-scale data collection.
•  Incremental Crawler: Collects updated content by revisiting previously crawled pages.
• Real Time Crawler: Monitors changes that occur instantaneously on the web.

Application Areas

Crawlers are used not only in search engines but also in many other fields. Widely used in academic studies, social media analysis, price comparison sites, cybersecurity applications and big data analysis, these tools are one of the key components of fast and efficient access to information. For example, news agencies or social media analysis platforms utilize real-time crawlers to gather instant information on specific topics. Platforms operating in the e-commerce sector use crawler systems to track competitors' prices.

Challenges and Ethical Issues

The development and use of crawler systems brings with it many technical and ethical issues. On the technical side, issues such as scalability, bandwidth limitations and robot.txt file compatibility come to the fore. On the ethical side, issues such as copyright, data privacy and server load are among the controversial aspects of crawlers.

Robots Exclusion Protocol (robots.txt) files are used to determine which pages of websites can and cannot be crawled. It is both ethically and technically important for crawlers to follow these rules. However, some crawler systems may cause legal and ethical problems as they collect content without complying with these limitations.

Current Developments and Future Perspective

Today, with the development of technologies such as artificial intelligence and machine learning, crawler systems are becoming more intelligent. Especially with the integration of natural language processing techniques, crawlers are able to analyze not only links but also the context of content. This enables more effective and meaningful data collection.

Furthermore, with the proliferation of distributed systems and cloud-based architectures, the performance and scalability of web crawlers has greatly increased. For example, BUbiNG, an open source project, is a distributed crawler system that can collect data at high speed and at scale.