Machine Learning for Talent Analytics: Unveiling Competency Indicators in Live Streamer

Abstract

The burgeoning live-streaming industry has become a transformative force in business, prompting a reevaluation of competency requirements for live streamers. However, there is still a lack of studies that focus on the objective assessment of live streamer competency indicators. This study aims to determine the key competencies of live streamers by utilizing machine learning algorithms for topic modeling. We identified seven core competency indicators for live streamers from 8,743 job advertisements from China's leading job search website, Kanzhun Limited. The top three competencies are "Interaction and Adaptability", "Marketing and Planning Skills", and "Talents and Specialties". The results also indicate that large companies prioritize operational and review abilities, while small companies focus on resource development. Moreover, part-time roles value talents and specialties, whereas full-time positions emphasize marketing and planning skills alongside operational and review abilities. This research provides theoretical insights into competency modeling within the live-streaming context and offers practical implications for talent acquisition and development in the industry. The findings suggest that organizations should tailor their recruitment strategies to align with the specific competencies required for different roles and organizational sizes.

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