Data mining application for cyber space users tendency in blog writing: a case study

TL;DR

This study analyzes the blogging tendencies of users in a specific region using data mining techniques, achieving over 82% accuracy in predicting future blogging behaviors to inform strategic decisions.

Contribution

It introduces a data mining approach using decision trees to predict user blogging tendencies with high precision in a specific regional context.

Findings

Achieved over 82% prediction accuracy.

Identified key factors influencing blogging tendencies.

Demonstrated effectiveness of decision trees in user behavior prediction.

Abstract

Blogs are the recent emerging media which relies on information technology and technological advance. Since the mass media in some less-developed and developing countries are in government service and their policies are developed based on governmental interests, so blogs are provided for ideas and exchanging opinions. In this paper, we highlighted performed simulations from obtained information from 100 users and bloggers in Kohkiloye and Boyer Ahmad Province and using Weka 3.6 tool and c4.5 algorithm by applying decision tree with more than %82 precision for getting future tendency anticipation of users to blogging and using in strategically areas.