There is a good chance that you or someone you know uses social media.
Over half of the world’s population uses at least one social media website. Whether through Facebook, Twitter, Youtube, etc., social media provides an opportunity to connect with others more efficiently than ever.
Social media platforms need technology that keeps up with massive amounts of users. That’s where artificial intelligence comes in. With AI, social media platforms can keep up with monitoring their platform and curating content that users are most likely to enjoy and stay on the platform.
AI has become an essential aspect of social media sites in many ways, which is why many software engineers can make up to six figures a year.
Here is how the five most prominent social media sites implement AI to improve their platform:
With over 500 hours of video footage uploaded to Youtube every minute, it may prove challenging for employees to regulate the massive amount of content. Google (Youtube’s parent company) has introduced a new “trashy video classifier” system entirely operated by AI.
Youtube has faced controversies with troubling content uploaded to the platform. One controversy, known as “Elsagate”, involved a plethora of inappropriate videos disguised as being “child-friendly” uploaded to the Youtube Kids website.
Google’s AI system is capable of:
- Scanning Youtube’s homepage for troubling content.
- Analyze videos for misleading titles/content.
- Review reported videos by users.
Youtube’s video analysis technology is essential to manage the workload of monitoring content and drawing advertisers to the website.
In 2018, around a dozen mob lynchings occurred in India fueled by rumors circulating around Whatsapp involving child trafficking and organ harvesting. These rumors were simply not true and innocent people’s lives were lost.
When a user sends circulating information to Maldita’s Whatsapp number, the automated bot will analyze the content and provide the previous fact-checked articles on the information. Or the bot will notify journalists if what is sent is not fact-checked.
The AI bot is designed to regulate “fake news” by automatically analyzing content that coincides with Maldita’s previous fact-checks. Bots like these help platforms control false content that could potentially become dangerous.
With 2.9 billion monthly users, Facebook has become a giant in social media platforms. Meta (formally known as Facebook) has been shown to push boundaries with AI implementation to run a successful website.
One way Meta uses AI to understand its Facebook users is through Deeptext, a deep-learning text-based engine.
- Understand textual contexts of posts with “near-human” accuracy
- Analyze around 20,000 posts per second
- Pick up on slang words and understand 20+ languages
By converting words into a computer algorithm, Deeptext can understand the similarities of words based on the integers assigned to them. Deeptext enhances the Facebook users’ experience by comprehending their posts and, based on that, provides desirable content and product suggestions for them.
If you want to experience opinions and news from around the world, Twitter is the social media platform to visit.
Twitter engineers now use deep learning technology to improve their algorithms and provide content catered explicitly to users.
The technology considers many factors when it designs a user’s timeline. This includes the tweet’s overall engagement, the author of the tweet and their relationship with the user, and the type of tweets the user has engaged with in the past.
Although the concept seems relatively simple on the surface, the intricacies of designing the unique timelines of 330 million monthly users can realistically only be achieved using AI software to reduce workload and provide efficiency.
Instagram is a visual social media platform with users typically portraying messages through images only. Also, users can create short videos like Reels and stories by utilizing various tools like Instagram story makers.
To enhance the visitor’s experience, Instagram implements machine learning by analyzing data around posts and determining whether to include them in their algorithm.
By using insights (or “signals”) of a post, the ML algorithm ranks the publications according to:
- The popularity of a post
- How many times a specific user has interacted with another user
- How much time an Instagram user spends on different pages
- History of a post’s interaction
By analyzing these “signals,” Instagram can keep users happy by providing content people want to see.