Web Scraping Social Media Using Support Vector Machine (SVM)
Year: 2024
Type: conference-paper
Abstract: At present days the Social Media Applications became one of the most important methods for marketing of goods, merchandise and emporiums. Especially the information access is easier for the users by using these applications. Sometimes analyzing these information takes a hard time and effort, besides it could need plenty of time to be quantified and evaluated. The most used social media application by the communities around the world is Facebook. By using Facebook Scraper application for windows, we scraped the pages information for marketing fields such as (cloths, cafés, cars, clinics and other companies). We used Support Vector Machine for classifying the Marketing Facebook pages. The aim of this work is to check the most pages or items that people prefer depending on the number of likes and follows, and also find the most popular interests and classify them into groups for analysis, we chose Iraq country as a case study for this paper and we gained great results for this work.
Language: English
Topic: Web Data Mining and Analysis
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4409495956