Artificial Intelligence Enabled, Social Media Leveraging Job Matching System for Employers and Applicants

Social media is increasingly becoming a window to the user\u27s 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

Enhanced Algorithmic Job Matching based on a Comprehensive Candidate Profile using NLP and Machine Learning

We propose to aid the hiring process by automatic profiling of a candidate’s social media presence and using it in conjunction with their resume and other information to suggest an employability score and an emotional intelligence indicator. Algorithmic hiring usually supports the hiring company and does not factor in social media presence of the candidate. The work we propose in this paper can also be used by the job seekers to evaluate their chances and uses a comprehensive profile of the candidate. Our approach uses social media profiling using APIs and web crawlers, evaluating soft skills, shortlisting candidates based on keywords, skill-set, and educational requirements and suggesting a match using Machine Learning and NLP techniques. The resulting application provides a faster, accurate, efficient, and relatively bias-free recruitment process to the companies and to the job seekers