Web scrapping using python and sentiment analysis

Web scraping is a powerful technique used to extract data from websites, and when combined with Python's BeautifulSoup library, it becomes an efficient tool for data collection and analysis.BeautifulSoup simplifies the process of parsing HTML and XML documents, enabling users to navigate and extract the desired content with ease.In the context of sentiment analysis, web scraping plays a crucial role in gathering large volumes of text data from sources such as social media, review websites, and blogs.This data is then processed and analyzed to determine the sentiment-positive, negative, or neutral-using natural language processing (NLP) techniques.By leveraging Python's BeautifulSoup, developers can automate data extraction, clean the collected data, and feed it into sentiment analysis models.This integration of web scraping and sentiment analysis provides valuable insights into public opinions, customer feedback, and market trends, making it a critical tool for businesses, researchers, and analysts in decisionmaking and strategy development.

Publication Details

Journal
IJARCCE
Published
2025-01-27
DOI
https://doi.org/10.17148/ijarcce.2025.14131
Primary Topic
Web Data Mining and Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Web scrapping using python and sentiment analysis

IJARCCE
Web Data Mining and Analysis
article

Web scrapping using python and sentiment analysis

article en

Abstract

Web scraping is a powerful technique used to extract data from websites, and when combined with Python's BeautifulSoup library, it becomes an efficient tool for data collection and analysis.BeautifulSoup simplifies the process of parsing HTML and XML documents, enabling users to navigate and extract the desired content with ease.In the context of sentiment analysis, web scraping plays a crucial role in gathering large volumes of text data from sources such as social media, review websites, and blogs.This data is then processed and analyzed to determine the sentiment-positive, negative, or neutral-using natural language processing (NLP) techniques.By leveraging Python's BeautifulSoup, developers can automate data extraction, clean the collected data, and feed it into sentiment analysis models.This integration of web scraping and sentiment analysis provides valuable insights into public opinions, customer feedback, and market trends, making it a critical tool for businesses, researchers, and analysts in decisionmaking and strategy development.

IJARCCEVol. 14(01)
Openalex Percentile: Top 98%
Web Data Mining and Analysis
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