An Implementation of Web Scraping IMDB Website

Web scraping is a powerful technique for extracting data from websites, and it has numerous applications in fields such as data science, market research, and business intelligence. In this article, web scraping is applied to extract data from IMDb (Internet Movie Database), the popular online database of movies, TV shows, and other entertainment content. The goal of this system is to collect a comprehensive dataset of movies and TV shows from IMDb website, along with their associated metadata such as ratings, genres, cast and crew and plot summaries. This automates the data collection process, creates charts/visualisation, displays the distribution of movie ratings, the most popular genres, the top-rated actors, or the most profitable movies. Python and the Beautiful Soup library files are used to extract the data, and then store it in a structured format and also into a MYSQL server database. Extracted ratings are analysed with different parameters of movies. It is found that this system followed a robust technique with DOM parsing, Tree traversal algorithms, CSS selectors, Xpath expressions and finite automata. Results are analysed with respect to extraction of required parameters.

Authors

Institutions

Publication Details

Published
2024-10-15
DOI
https://doi.org/10.1109/icses63445.2024.10763176
Citations
1
Primary Topic
Video Analysis and Summarization
Type
article
Field-Weighted Citation Impact
0.25
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An Implementation of Web Scraping IMDB Website

Sumathi Pawar, Geetha Laxmi, Vasanth Nayak, B. S. Vandana
1 citations
Video Analysis and Summarization
0.25
article

An Implementation of Web Scraping IMDB Website

Sumathi Pawar, Geetha Laxmi, Vasanth Nayak, B. S. Vandana
article en
1 citations

Abstract

Web scraping is a powerful technique for extracting data from websites, and it has numerous applications in fields such as data science, market research, and business intelligence. In this article, web scraping is applied to extract data from IMDb (Internet Movie Database), the popular online database of movies, TV shows, and other entertainment content. The goal of this system is to collect a comprehensive dataset of movies and TV shows from IMDb website, along with their associated metadata such as ratings, genres, cast and crew and plot summaries. This automates the data collection process, creates charts/visualisation, displays the distribution of movie ratings, the most popular genres, the top-rated actors, or the most profitable movies. Python and the Beautiful Soup library files are used to extract the data, and then store it in a structured format and also into a MYSQL server database. Extracted ratings are analysed with different parameters of movies. It is found that this system followed a robust technique with DOM parsing, Tree traversal algorithms, CSS selectors, Xpath expressions and finite automata. Results are analysed with respect to extraction of required parameters.

Nitte University (IN)
Openalex Percentile: Top 44%
Video Analysis and Summarization
0.25
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.