Image Analytics – How it can Change Social Media Experience
Social media has a strong influence on modern-day life. More than 3 billion people worldwide use some form of social media, with at least 11 new members joining these platforms every second. The experience is getting more immersive every day, with giants like Facebook, Twitter, Instagram, Snapchat, etc. striving to offer a streamlined, smoother, and better end-user interface. One key aspect of bringing such changes is to implement better image analytics and recognition technology.
Social media platforms witness an overwhelming number of photographs shared across them on an everyday basis. Studies show that at least 3.2 billion photos are uploaded on these sites daily, and enjoy over 150 times more shares than only text-based posts. These make image analytics the perfect tool to enhance the social media experience.
Image analytics – what is it?
Image analysis is a branch of artificial intelligence that deals with analyzing pictures and other rich media formats. These use various types of processing techniques to extract actionable and meaningful information from images. With the advent of better and more powerful AI and handheld devices, image analytics has become incredibly rich, able to understand the human sentiment and brand perception from pictures.
An essential addition to social media
AI integrated social media platforms use image analytics to understand people’s faces, background, writing, brand logo, and various other types of information from a picture. Images generally garner a significantly higher engagement rate; posts with images generally gather almost 2.3 times more engagement than ordinary text-based posts.
Image recognition and analytics are widely used to increase order in social media platforms. Platforms like Twitter, Facebook, and Instagram can accumulate millions of posts every minute. AI-based image analytics programs can sift through such large volumes and detect the relevant content with ease.
Companies are using such systems to locate significant interactions, identify and take action against spams, and pinpoint correct interactions. These improve the user experience, focus attention on the vital information, and help an individual respond to them accordingly.
High success rate
Image analytics systems come with an extremely low error rate. A recent MSIT study showed that error rates could be as low as 0.23% even when operating on normal operational speed and processing power. These aspects are critical to addressing user insights on social media. A lag-free interface that can locate the relevant information in a vast ecosystem is essential to weed-out unwanted content from social media platforms.
Image analytics has brought significant changes to how everyone uses different social media platforms. Users can now browse through the vast network without worrying about unwanted exposure to harmful content. Such censorship can effectively bring an end to malicious practices on social media platforms as well as systematic targeting of individuals or communities.