10 Applications of Machine Learning in Social Media

Social media is everywhere. The power of social networking sites is as strong as fire. With over 2 decades gone into the making and building of social media, the world today is more connected than it ever was. 

 

In the pre-social media world, people could only rely on telephones, pagers, or even pigeons in the archaic era to communicate and mediate with one another. As social media platforms like Facebook emerged on the surface, people discovered newer ways to explore methods of communication. 

 

What seemed to be a one-way communication process quickly converted into a cross-communication channel. The importance of social media is quite evident with the widespread usage and participation that people witness worldwide. 

 

That said, social media is incomplete without discussing its backbones - advanced technologies like artificial intelligence and machine learning. With the aid of machine learning, social media has not only proliferated in terms of its reachability but it has also unfolded new possibilities across various platforms. 

 

A typical example of this stance is the conventional use of social media. While social media sites were earlier used as means of communication, they are today used for a variety of purposes like communication, marketing, promotion, and advocacy. 

 

As we speak of social media and its evolution, someone out there is busy discovering what more could be done with social media sites. That is the true power of these platforms. Their journey never stops and platforms like Instagram, Facebook, and Twitter will always be on the rise with the simultaneous spike in the use of the internet.  

 

Top Applications of Machine Learning in Social Media 

 

Let us now understand with the help of this segment the top 10 applications of machine learning in social media. 

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Applications of Machine Learning in Social Media

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1. Visual Recognition

 

One of the best ways to implement machine learning techniques in social media is through visual recognition. By using machine learning algorithms, social media platforms are well capable of recognizing images without any auxiliary texts. 

 

This makes social media platforms helpful for companies and advertising professionals to look for searched images and queries. Furthermore, visual recognition also plays an important part in verifying user photos without revealing any personal information. 

 

This can prove to be effective for a variety of purposes such as when the consumers of businesses upload pictures of a product without clearly mentioning the product or brand name in the text. There is often a much higher span of user attention for Social Media Posts With Photos as opposed to posts that only contain text

 

2. Filtering Spam Content

 

This one comes in handy for social media sites considering that the current scenario is filled with such reports. Spam is present everywhere - calls, messages, texts, or even news. 

 

As content on social media spreads like a wildfire, it becomes very important to keep filtering and clearing spam content from such platforms at regular intervals. Thus, software applications customized with machine learning training can be deployed to filter spam content across various horizontal and vertical sections. 

 

This helps in constant regulation of the social media space which, in turn, ensures that no spam content reaches the innocent audience. 

 

3. Fake News Identification

 

Just like spam content, fake news is also omnipresent. The only distinguishing factor between the two is that fake news is much more harmful and exploitative in nature. 

 

To identify fake news, social media sites take aid from machine learning tools and techniques so that pre-recorded data can help tools identify similar content. This is not an easy task. 

 

Thus, both technical and manual labor have to be invested in carrying out this task. As opposed to traditional times where fake news could easily be circulated in a non-regulated social media space, today the scenario is completely different. 

 

With the help of strict reporting measures where even a layman can report fake news or suspicious content, fake news can instantly be blocked from any channel of communication, preventing the spread of fake news by a notch. 

 

4. Sentiment Analysis

 

The next use of machine learning in social media is concerned with sentiment analysis. Artificial intelligence is known as the concept that instills human-like intelligence in computers so that they can perform similar functions. 

 

While this type of intelligence is usually concerned with technical, mathematical, and analytical intelligence, computers usually lack emotional intelligence. This bars them from identifying sentiments behind a text or a message. 

 

However, with the development of emotion AI or opinion mining, machine learning can be induced among social media regulators to perform sentiment analysis using various social media sentiment analysis tools. 

 

Simply put, machine learning enables computers to identify emotions behind specific content put up by a user on social media platforms. 

 

Sentiment analysis can be applied by businesses in social media as well as customer support for gathering feedback on a particular new product, design or service. It can also be applied to help businesses ascertain how their target audience feels about their competitors and their perspective on the present trending issues in the industry.

 

5. Chatbot System

 

We have all been there, chatting with robots, knowing that the world has advanced so much that robots are providing us with sought-after solutions. Be it e-commerce or social media, chatbot systems are a renowned application of machine learning. 

 

By inducing human-like intelligence and other traits in bots, computers have become capable of carrying out simple yet crucial tasks like customer service and feedback resolution. 

 

By using chatbots to converse with users over social media platforms, machine learning has taken the extent of social media to newer heights. 

 

6. Market Segmentation

 

The next application of machine learning is that it helps social media sites in market segmentation. Since social media has opened up for marketing and digital advertising, it is important for businesses to segment the digital market strategically. 

 

This helps businesses to grow and generate revenue. Using market segmentation, not only social media platforms can become a better place for promoting businesses, but they can also contribute to the role of big data in social media by accumulating humongous data. 

 

While machine learning tools can be customized to keep a track of emerging market segments, usually social media sites witness a cross-culture of target audiences. 

 

What’s more, social media sites can also target specific customers through sponsored advertisements and posts that can indirectly help hit the target.  

 

7. Performance Metrics

 

One of the biggest benefits of Machine Learning in social media, or even machine learning, is that it can lay out some very useful performance metrics that can indicate the growth of such sites. 

 

For instance, businesses or influencers on Instagram can evaluate their performance or reach on the platform using built-in metrics like engagement rate, followers, and comments. 

 

With the emergence of full-time careers across social media sites, performance metrics have become crucial criteria to evaluate how well social media accounts are reaching out to others. 

 

With the help of machine learning algorithms, social media platforms can also regulate the activity of all participants. Apart from performance evaluation, social media monitoring is equally an essential facet of its application in this field. 

 

8. Marketing Strategies

 

Adding to the use of machine learning in social media in the marketing sector, social media marketing has become a full-time career opportunity that people are now taking up. 

 

That said, marketing strategies on social media accounts have taken an interesting turn. From reaching out to influencers personally for collaborations to launching engaging advertising campaigns, businesses present on social media accounts are actively promoting their products and services to their target audiences. 

 

In addition, chatbots are also a part of the marketing strategies employed by businesses on social media platforms. 

 

Some of the most popular social media marketing strategies involve engaging stories wherein businesses put up poll stories, question/answers, and yay/nay stories to collect useful feedback from their potential customers. 

 

9. Network Recommendations

 

When machine learning is combined with other intelligent technologies like natural language processing (NLP) or artificial intelligence, social media can be enhanced and elevated in terms of its capability. 

 

One of the most typical examples of this duo is network recommendation. From ‘suggested friends’ to ‘suggested accounts’, network recommendations are a striking feature of social media platforms that help people connect and communicate faster and in a better way. 

 

This has substantially increased the quality of social media sites by exploring mutual contacts from a person’s list of friends and known people. 

 

Other features include the most contacted with and the least contacted with people from an individual’s following list. Such features only filter the most interactive elements in an individual’s social media account. 

 

10. Paid Promotions

 

The last of all applications of ML in social media revolves around the concept of paid promotions. Well, to begin with, paid promotions are paid advertisements that social media platforms push more than they do so with organic advertisements. 

 

The fact that money has been paid to promote such ads and related businesses is what makes paid promotions such a striking feature of social media. 

 

However, the rock behind this concept is that machine learning empowers such platforms to find the right target audience and constitute such promotions in a way that users get attracted to them and feel like engaging with such elements. 

 

For all we know, users spend a substantial amount of time on social media scrolling through reels and stories of others. This also involves coming across paid content promotion and sponsored ads that tend to sell a service or a commodity at its best. 

 

Also Read | Basics of Machine learning: Types and Applications

 

Future of Social Media

 

The future of social media is full of turning points as it has turned out to be in the past decade. From just a gossiping place to a place where cultures could cross-connect, social media has truly turned out to be social in every aspect. 

 

With the support of ML and artificial intelligence, social media can advance a lot more towards the direction of responsible communication, and active advocacy, and yield good results for the betterment of society. 

 

Even though it is a place for people to spend their leisure time, it can soon convert into a platform for raising voices, participating in crucial discussions, and bringing policies into action. 

 

As is the case, social media has already evolved into a heating pot of conflicts, communication, and ideas that need to be regulated and eased down so that people can do their best when they have this weapon in their hands.