Use of AI for Personalized Content in Social Media
Social media has become a ubiquitous part of our everyday lives. Beyond the early days of MySpace and Digg, the internet has seen a variety of platforms that cater to everyone’s specific interests and communities from the globally recognized Facebook to the more niche groups on Reddit that can become incredibly specific.
The advent of artificial intelligence (AI) has only made social media stronger by providing users with more access to personalized content. Not only does this lead to more enjoyable user experiences, but it also helps creators focus on the content they develop and the success of the platform as a whole.
How AI Contributes to Personalization
AI and machine learning are specifically adept at analyzing user activity, and identifying how they interact with content by measuring their clicks, likes, shares, comments, and more. Many platforms, like YouTube, even measure the duration a user spends on certain videos and mark the most replayed moments to provide creators with better insights into their most successful content.
AI uses this user-generated data to provide creators with context, helping them recognize what their viewers enjoy most, whether it be a certain type of joke, a graphic used in the video, or certain clips that provide additional context. Together, creators can develop more specific content with AI’s insights while machine learning algorithms create recommendation feeds that suit a user’s unique taste.
Benefits of AI-driven Personalized Content
AI creates a variety of benefits for all parties involved on social media including content creators, users, and product marketers. The amount of exposure generated on these platforms can create huge spikes in traffic without patronizing the user who is seeking enjoyable content.
Enhancing engagement: Traditionally, content online and on television was meant to appeal to the largest, most general audience possible, but with the rise of social media, content creators have been able to create more tailored material using metrics gathered by AI algorithms.
Increasing relevant content: Recommendation feeds are powerful algorithms that are able to push relevant content towards users. This helps reduce the time it takes for users to find content that they want to engage with, speeding up their chances to find material that they enjoy most from their favorite creators.
Boosting marketing strategies: Marketers also have a lot to gain from personalization by sponsoring videos with advertisements for products that are more relevant to their users.
Real-world Examples of AI in Personalized Content
AI algorithms can be observed all over social media and not just in one way. Many platforms have various algorithms to help with different sections of their websites, but some of the most well-known examples include:
Facebook News Feed: Meta is a social media titan and must filter event content to an extreme degree for every user based on their interest, likes, and connections to other people and pages.
TikTok For You: TikTok’s algorithm has quickly become one of the most powerful tools seen in social media, filtering through countless amounts of videos for a growing user base that is extremely popular with younger demographics.
YouTube Video Recommendations: YouTube sorts through videos based on a user’s list of channel subscriptions and how often they frequent certain topics and videos. The algorithm compliments the scheduled release of content from creators too.
Challenges and Considerations
Recommendation Algorithms have received considerable pushback following the election of President Donald Trump after his repeated claims of fake news and the use of Twitter. AI algorithms quickly began to recycle highly politicized content without being able to verify them, causing people around the United States to become vehement against each other.
This troubling aspect of AI became worse over time as social media platforms like Facebook and Twitter began to see scores of bots flooding their platforms. These bots would post content constantly throughout the day that baited enraged users with personalized graphics and videos that were largely false, causing platforms like Twitter to succumb to pressure and lose a majority of their user base due to the frustration.
Future Trends and Predictions
Although social media’s use of AI has gathered a large amount of criticism since 2016, activity on social media has not receded. TikTok’s rise in popularity, which was the fastest application to reach 100 million users before ChatGPT took its place, shows that user activity merely migrated to a new platform.
Some platforms like YouTube, which is the second largest search engine on the internet behind Google, have also continued to be successful. However, new AI algorithms are being used to prevent ad-blocking extensions, forcing users to engage with personalized advertisements. While ads are not favored by users at all, their personalized nature shows that AI will remain a constant influence in the development of social media content.
