Employee performance assessment in virtual organization using domain-driven data mining and sentiment analysis

The change of society from an industrial based society to a service based and even to an information based society has generated a particular group of workers; people, who work in their way through information, solve problems in their own way form their own place. This category of workers has changed the overall productivity and profitability graph of the organization which stands for a task, project or permanent organization, not necessarily centralized and dependent called Virtual Organization. Virtual Organizations are geographically dissipated; therefore assessing the performance of the workers working in it is an important issue. Assessment is a dynamic process, thus the aim of the studies is to evaluate the performance of employees in virtual organization and predict the quality, productivity output and potentiality of the employees by various performance measures which will enable the superior to take proper decisions and understand patterns for employee's motivation, satisfaction, growth and decline of both the employees and the organization itself. A hermeneutic analysis process is carried out in this research which includes employees' practices, culture, work of art and text in the organization. The study involved to propose a employee performance assessment system with phenomenological Domain Driven Data Mining (D3M) approach additionally using 360 Degree data mining for the extraction of unidentified patterns in employee performance when assessed across various parameters. The system is also bounded by the Sentiment Analyzer to check perception of the superiors towards their employees' task and work structure along with the integration of Fuzzy Group Decision Support System which works as multi-factorial evaluation unit.