Assessing Candidates’ Experience through Sentiment Analysis

Assessing candidates’ experience through sentiment enalysis

Our client encountered a substantial challenge during their recruitment process – the task of analyzing a considerable amount of  feedback data gathered through a survey. To derive valuable insights from this data and improve the overall recruitment experience, they turned to our Data Analytics team for a solution.

Our team suggested conducting sentiment analysis and utilizing AI-powered text summarization techniques to extract key insights from candidate comments.

The analysis provided the client with a comprehensive overview of candidate sentiments, enabling them to re-evaluate their recruitment procedures and make data-driven decisions to improve the candidates’ experience.

Client Challenge

The client collects large amounts of candidates’ feedback data during the recruitment process and was looking for ways to analyze the data received through a survey. The firm was looking for:

  • Automated tool to analyze candidate feedback as opposed to doing it manually.
  • Generate relevant insights from the analyzed data to improve the candidate recruitment experience.

Our Solution

Infomineo’ s Data Analytics team addressed the client’s challenges by:

  • Conducting sentiment analysis using the state-of-the-art language model Roberta to analyze candidate feedback and extract the overall sentiment.
  • Using AI-powered text summarization through Open AI’s GPT-3 to extract key insights from candidate comments, focusing on areas of concern such as discrimination and unprofessionalism and showing the specific comments.
  • Creating a Dashboard : Allowing for easy filtering of feedback and candidate sentiment.

Outcome

  • The analysis provided the client with a comprehensive overview of candidate sentiments, enabling them to identify areas of strength and areas for improvement in the recruitment process.
  • In addition, the results of the analysis enabled the client to re-evaluate its recruitment procedures and make data-driven decisions to improve the candidate experience at the global, regional, country and departmental level.
  • The results also helped the client develop new perspectives on the power of AI-powered tools in streamlining and enhancing the analysis of large datasets.

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