Natural language processing or NLP is computer technology to understand the human’s natural language. NLP is the branch of artificial intelligence that deals with natural language to interact between computers and humans.
Most NLP algorithms used to drive meaning and new information from human languages. For example, sentiment analysis, text categorization, machine translations are some of the applications of text analytics.
The importance NLP for Human Resource Management
Natural language processing (NLP) algorithms take text, analyze them and create a higher level of detail and accuracy from them. NLP can use historical text data to show managers better results and help them getting better decisions by spending less time.
The benefits of using NLP is many, corresponding to varying levels of engagement and investment by HR.
In 2019, more than 473,400 tweets and more than 100 million messages have been sent every minute globally. NLP algorithms make it possible to analyze this amount of data in a short amount of time and bring many details information to the business owners about their customers’ and employees’ attitudes on social media. The process can start with generic text analytics (sentiment analysis), continue with advanced insights (via computational linguistics models) and can even include potential semi-automation.
The most important use-cases of NLP in HR
Recruitment: NLP algorithms can select and rank candidates based on their abilities and filter them for HRs and other departments automatically based on the applicant’s resume and motivation letter.
Employees Feedback: By having so many text feedback, managers and HR have to spend a lot of time to go through each of them to find out the main area and purpose of the feedback. Sentiment analysis and topic categorization can help them in this area to get a good quick insight on the whole feedback and understand what is the main topics and feelings of them without spending time and energy.
Social media analysis: NLP makes It possible to monitor employee social behavior, interests, and perception to identify opportunities or issues inside the company.
These days the amount of text-data at organizations is increasing rapidly. The HR department is one of the main resources in gathering and analyzing these data and using them to get better decisions for the company.
In ComeMit, we are using cutting edge algorithms of text mining and text analytics solutions to help companies spend less time understanding their text-data and get better decisions based on their people’s feedback.