[Practical Exercise] Practical Case Analysis: Using Web Crawlers to Obtain Movie Review Data and Perform Sentiment Analysis

# 1. Fundamentals of Web Scraping Technology

Web scraping technology is a method of automatically fetching data from the internet. It involves simulating web browser visits, parsing page content, extracting desired information, and storing it locally or in a database. Web scraping is widely used in search engines, data mining, market research, ***

***mon types of web scrapers include general-purpose, vertical, and incremental web scrapers. General-purpose web scrapers aim to collect all content on the internet, while vertical web scrapers focus on specific domains or websites. Incremental web scrapers periodically fetch updated content from websites to keep data current.

Web scraping technology involves several aspects, including target website analysis, data structure design, web scraper framework selection, web scraping program coding, data cleaning, and preprocessing.

# 2. Web Scraping Practical Exercises

### 2.1 Target Website Identification and Data Structure Determination

**Target Website Identification**

The first step in practical web scraping exercises is to identify the target website. The selection of the target website should be based on specific needs and research purposes. For instance, if you want to collect reviews about a specific product, the target website could be Amazon or another e-commerce platform.

**Data Structure Analysis**

After determining the target website, you need to analyze its data structure. Data structure refers to the organization of data on the website. Understanding the data structure is crucial for writing effective web scraping programs, as it can help you determine which data elements to extract and their relationships.

### 2.2 Selecting Appropriate Web Scraping Frameworks and Tools

**Web Scraping Frameworks**

Web scraping frameworks provide a set of pre-built components that simplify the development process of scraping programs. Popular web scraping frameworks include Scrapy, Beautiful Soup, and Selenium. These frameworks offer various features, such as:

- Web page parsing
- Data extraction
- Concurrent request handling

**Web Scraping Tools**

In addition to web scraping frameworks, many tools are available to simplify scraping tasks. These tools include:

- HTTPie: A command-line tool for sending HTTP requests
- cURL: A command-line tool for transferring data
- Fiddler: A tool for debugging and analyzing HTTP traffic

### 2.3 Writing Web Scraping Programs and Optimizing Performance

**Writing Web Scraping Programs**

Using the selected web scraping framework and tools, you can write scraping programs to extract data from the target website. Web scraping programs generally include the following steps:

1. Send HTTP requests to fetch web pages
2. Parse web pages to extract the desired data
3. Store the extracted data in a database or file

**Optimizing Performance**

To improve the performance of web scraping programs, you can adopt the following optimization measures:

- Use multithreading or multiprocessing to handle requests in parallel
- Use caching to avoid duplicate requests
- Limit request frequency to prevent server overload
- Use anti-scraping measures to bypass the website's scraping detection mechanisms

### 2.4 Data Cleaning and Preprocessing

**Data Cleaning**

Data extracted from target websites often contain noise and inconsistencies. Data cleaning involves removing or correcting these errors to ensure data quality. Data cleaning techniques include:

- Removing duplicates
- Handling missing values
- Standardizing data formats

**Data Preprocessing**

Data preprocessing is the process of transforming data into a format suitable for analysis. Data preprocessing techniques include:

- Feature extraction: Extracting useful features from raw data
- Normalization: Scaling data to a similar range
- Dimensionality reduction: Reducing data dimensions to improve efficiency

# 3. Fundamentals of Sentiment Analysis

### 3.1 Concepts and Methods of Sentiment Analysis

**Concept**

Sentiment analysis, also known as opinion mining, is a natural language processing technique used t