Proceedings - 2022 International Conference on Recent Trends in Microelectronics, Automation, Computing and Communications Systems, ICMACC 2022
Social media is increasingly becoming a window to the user's personality. Hiring the right candidate is a formidable task for any organization and particularly in the highly competitive software industry. This paper presents a machine learning and natural language processing based system to leverage social media to assess job applicants for their suitability for a given job. We use LinkedIn profiles to assess the technical suitability and combine Twitter posts with them to assess the emotional intelligence of the applicant. The system thus indicates both the technical and soft skills perspective of the job applicants. The system can be used by both prospective employers and employees. Employers can use it to shortlist job applicants and prospective employees can use it to evaluate their chances, retrospect, and take any corrective action. The results from the created system are encouraging.
San José State University
Hiring, Machine Learning, Natural Language Processing, Regression, Social Media
Applied Data Science
Vishnu Pendyala, Nishtha Atrey, Tina Aggarwal, and Saumya Goyal. "Artificial Intelligence Enabled, Social Media Leveraging Job Matching System for Employers and Applicants" Proceedings - 2022 International Conference on Recent Trends in Microelectronics, Automation, Computing and Communications Systems, ICMACC 2022 (2022). https://doi.org/10.1109/ICMACC54824.2022.10093323