Performance Evaluation in Virtual Organizations Using Data Mining & Opinion Mining

Performance Evaluation in Virtual Organizations Using Data Mining & Opinion Mining

Abstract:

Performance evaluation in virtual organizations is crucial in the transition from industrial to knowledge era. This project aims to create a system that evaluates company employees from remote and branch locations. Virtual organizations, where employees work from home or different company branches, are growing in IT. Enhancing productivity and profitability requires evaluating employee performance across locations. Virtual organizations make loyalty and role-related behavior monitoring difficult. Misjudging performance in such environments can harm employees.

Our system uses phenomenological domain-driven data mining (D3M) with 360-degree data mining for objective measurement and opinion mining for subjective measurement to address this issue. The system analyzes employee messages for keywords to assess performance. The system mines a database of keywords to classify messages by data, domain, and social factors.

Low-performing employees ask questions, while high-performing employees use domain or data-related keywords. However, employees who use many unrelated social keywords will be rated poorly. The system will monitor workers online. The D3M approach helps practitioners evaluate virtual employees’ performance.

Introduction:

Performance evaluation in virtual organizations is becoming more important as business moves from the industrial to the knowledge age. Virtual organizations, where employees work remotely or from different company branches, make accurate performance evaluation essential. Traditional performance evaluation methods, which measure loyalty and role-related behaviors, are unsuitable for diverse employees. Virtual employees can suffer serious consequences from inaccurate performance assessment.

Objectives:

This project aims to create a system that uses data mining, specifically the phenomenological domain-driven data mining (D3M) approach, to evaluate virtual organization employees. The system uses 360-degree data mining and opinion mining to assess employee performance.

Project Details:

The proposed system will monitor virtual organization employee messages. Based on these messages’ keywords in a database, it will evaluate their performance. The system can evaluate employee performance by mining keywords and classifying messages by data, domain, or social factors.

Low performers send many questions. Using domain or data-related keywords extensively will boost performance. The system will also rate low performers who use many social-related keywords unrelated to work.

Online implementation allows real-time employee monitoring. Practitioners can evaluate virtual employee performance using the D3M approach.

Conclusion:

Performance evaluation in virtual organizations is crucial to knowledge-era business management. Remote and branch workers often fail traditional evaluation methods. Our project uses data mining methods, including phenomenological domain-driven data mining (D3M), to solve this problem.

The system evaluates employee performance objectively and subjectively by monitoring employee messages and keywords. This method improves productivity and profitability by revealing virtual employee performance.

Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.