5 Natural Language Processing Trends in 2021
When we think of computer science, namely Artificial Intelligence (AI), it’s easy to forget just how revolutionary it is.
Today, Artificial Intelligence can not only speak, write, listen and understand human language, it can also extract meaning from natural language to make informed decisions all thanks to Natural Language Processing. NLP is arguably one of the most exciting fields in AI and has already given rise to technologies like voice assistants, chatbots, translators, and many other tools that we use daily.
So, what is this branch of artificial intelligence and why does it matter?
What is Natural Language Processing?
Natural Language Processing is a field of AI that enables computers to analyse, understand and arrange human language. Natural language processing software continues to advance to better interpret the nuance, context and obscurities present within human communication.
NLP has already been adopted by many businesses that are driving results by drawing insights from large quantities of data while automating repetitive and monotonous tasks. Even in the wake of the pandemic, 53% of leaders indicated their NLP budget was at least 10% higher compared to 2019.
Natural Language Processing applications
Chatbots
If you’ve browsed or shopped online, you’ve likely interacted with chatbots. Chatbots are essentially AI-powered customer service representatives, or algorithms, that use natural language processing to be able to answer your query. Chatbots employ NLP to not only answer your questions but also provide accurate, automatic responses in real-time.
Email assistants
Auto-complete, spell check and auto-correct are all examples of NLP-enabled functions that assist email composition. Natural language processing is also employed by your email’s spam filter to help ascertain whether or not the email is junk mail or if it’s worth keeping.
eCommerce
When you shop online, NLP allows for superior search results that match your search intent. NLP is becoming more and more capable of deciphering search queries regardless of spelling mistakes or missing details, enabling users to get better results, faster. By searching online, users are feeding the customer data that helps retailers understand their preferences and habits; adding to the algorithmic, as opposed to human, handling of customer interactions.
Information extraction and analysis
Natural language processing can extract and combine information from an assortment of text sources including articles, news reports, user manuals, and more. What’s more, NLP can then use the information it gathers to make decisions and react based on algorithms.
5 Natural Language Processing trends in 2021
One thing is certain: NLP is only going to grow in 2021. Here are the 5 top NLP trends to look out for this year.
1. NLP will require a holistic approach
Organisations that understand how AI will work within a product, in addition to the technical talent needed to implement and scale an NLP project, will perform better from a business perspective. To stay competitive, all branches of an organisation will need to understand the advantages of integrating AI and how it will affect their role. The reason many projects fail is due to the lack of a holistic AI integration whereby product managers, designers, marketers, sales, etc. aren’t actively involved in its adoption. It’s the overall investment in education, time, energy and practice across the entire organisation that will distinguish its success in the coming year.
2. Increased customer service automation
For businesses everywhere, the pandemic has challenged them to deal with increasing ticket volume whilst providing fast responses to urgent queries. In 2021, organisations will continue to automate simple customer service tasks to help them handle bundles of customer queries quickly and efficiently. Integrating NLP tools with help desk software, for instance, can help automate tedious tasks like tagging and routing customer support tickets, enabling agents to focus on higher-value tasks.
With the advances in NLP technology as well as rising demand in customer service, we can also assume that there will be massive advancements in the next generation of chatbots. Chatbots this year and beyond will be able to hold more complex conversations, self-improve, and possibly teach themselves how to complete new tasks without prior training.
3. Multilingual offerings will grow
Only until recently, NLP support was limited to just a few languages including English and Mandarin. Today, multilingual models are now gradually being introduced to data scientists globally. Cloud providers can now offer NLP support in over 100 languages, and with the influx of new research advances, this will surely become the norm. The availability of many languages and more access to code ultimately helps level the playing field universally, allowing for a more varied and inclusive AI environment.
4. Social media monitoring
Opinion mining, or sentiment analysis, will play a major role in how businesses monitor their social media in 2021. Utilising NLP tools to gauge brand sentiment will enable organisations to gain real-time insights into how customers feel about their products or brand. NLP for social media monitoring can help companies locate opportunities for improvement, detect and proactively respond to negative comments, and gain a competitive advantage. Not only can you use sentiment analysis in social media monitoring for analysing the impact of your marketing campaigns, but you can also evaluate how customers react to company events, product releases, etc.
5. Advanced detection of fake news and cyberbullying
In recent years, fake news has largely crippled our understanding of factual validity. With NLP, it can reduce the amount of time and human effort required to uncover and prohibit the spread of misinformation and fake news. The need for this type of fake news regulation will only continue to increase, so we’ll definitely see more of it in 2021.
In addition to fake news detection and prevention, NLP also has the ability to detect cyberbullying in the form of hate speech and/or offensive and insulting language posted across social media. This will surely surface in 2021 as conversations regarding social media content regulation continue to increase.
Conclusion
NLP will only continue to benefit businesses as our reliance on, and understanding of, data shifts. With the amount of data at our disposal, it will be more and more pertinent to understand it, observe it, and in certain situations, censor it. Natural language processing will become more widespread in the years to come, as businesses reap the benefits it has to offer; from improving operations and reducing costs, to heightened customer satisfaction and more informed decision making.
