5 real-world applications of natural language processing (NLP)

Natural language processing (NLP) is a field of study that focuses on enabling computers to understand and interpret human language. NLP involves applying machine learning algorithms to analyze and process natural language data, such as text or speech.

NLP has recently been incorporated into a number of practical applications, including sentiment analysis, chatbots and speech recognition. NLP is being used by businesses in a wide range of sectors to automate customer care systems, increase marketing initiatives and improve product offers.

Related: 5 natural language processing (NLP) libraries to use

Specifically, this article looks at sentiment analysis, chatbots, machine translation, text summarization and speech recognition as five instances of NLP in use in the real world. These applications have the potential to revolutionize the way one communicates with technology, making it more natural, intuitive and user-friendly.

Sentiment analysis

NLP can be used to analyze text data to determine the sentiment of the writer toward a particular product, service or brand. This is used in applications such as social media monitoring, customer feedback analysis and market research.

A common use of NLP is sentiment analysis of the stock market, in which investors and traders examine social media sentiment on a particular stock or market. An investor, for instance, can use NLP to examine tweets or news stories about a specific stock to ascertain the general attitude of the market toward that stock. Investors can determine whether these sources are expressing positive or negative opinions about the stock by studying the terminology used in these sources.

By supplying information on market sentiment and enabling investors to modify their strategies as necessary, sentiment research can assist investors in making more educated investment decisions. For instance, if a stock is receiving a lot of positive sentiment, an investor may consider buying more shares, while negative sentiment may prompt them to sell or hold off on buying.

Can ChatGPT beat the stock market?

I used ChatGPT and programmed a script to read stock news, perform sentiment analysis, and then message me the results on Telegram every morning before the stock market opens. pic.twitter.com/heB3pGPwC0

— MARK LITTON (@mblitton) April 21, 2023

Chatbots

NLP can be used to build conversational interfaces for chatbots that can understand and respond to natural language queries. This is used in customer support…