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Machine Learning Usecase 08-Social media analysis

Machine Learning technology in social media allows machines to decide which advertisements are to be shown to which audience. They collect data from users, analyze it, find out their preferences and accordingly show advertisements which hold their interest.
Machine Learning Usecase 08-Social media analysis

Machine learning can analyze millions of posts on Facebook, Twitter, Instagram, read comments, and personal updates. Businesses keep up with customer feedback, track their brand health, and improve their reputation.

Machine learning allows systems not only to recognize words but understand the context behind them. For instance, “orange” can be used to describe a color or a name brand. As an owner, you’ll want to see the posts that fall under the second category – and ML makes it possible by analyzing the context of a message.

Emotional recognition

AI and ML analyze the context in which the brand’s name is used and compare a single message to millions of similar posts. Complex algorithms track the differences between happy, unhappy, interested, or sarcastic.

Unsupervised detection

Businesses use machine learning to know what their customers care about. Machine learning isn’t limited to pre-set values: in other words, it will show all results that fit the general context, not just what the business owner searched for. It’s possible to get unexpected results that fall out of your expectations.

Probyto AI allows organizations to build and manage such usecases and track the benefits of AI adoption in their businesses. Currently, FREE 60 minutes AI Consultation is being provided to the registered users in the Probyto AI Demo platform. If you haven't registered yet, register now to Probyto AI Demo.

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