How Does Social Media Use Machine Learning?
Popular social media platforms have quickly become marketing channels for brands of all sorts. They do this by use of machine learning (ML), which is a series of algorithms that give computers the ability to identify patterns in data and then classify them into groups or clusters. Social media websites use natural language processing (NLP) to gather clues about the user’s gender, age, location, preferences, etc.
How is Machine Learning & NLP Used In Social Media?
Machine learning is used in social media analysis because of the sheer volume of data social media activity produces every second. ML can process large amounts of data into algorithms and draw relevant conclusions from findings. Advanced web scraping tools are used by relying on keywords, for example, a brand or product name. The texts are important, but what is extremely helpful is to analyze the context of which the keywords are being used in. This is where NLP comes into play. NLP extracts meaning to unstructured text data. With NLP companies can conduct insights from social media feeds. Companies can gain insights into a customer’s satisfaction with a product through word association, positive or negative.
How Does Machine Improve Our Social Media Experience?
The insights gained through use of ML can help both businesses and customers meet their needs. A customer will receive targeted ads based on all the data gathered on them through all their social media activity, ML can also help businesses predict whether a person will act on the ads or ignore them. This is also used through recommended posts based on what might interest each individual user. Social media uses ML to improve user experiences, enhance social networking/marketing products, data privacy, and automate data. The insights drawn help average everyday people who would not otherwise have a platform, like movie stars and celebrities, to have a voice and influence others.
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