The Impact of Artificial Intelligence On Social Media

Humans For AI
Sep 26, 2019 · 4 min read

~ Peyton Wang

Today, consumers constantly interact with social media. Many of us may even say we are addicted to our screens. Companies are very eager to take advantage of our constant engagement with platforms such as Facebook, Twitter, and Snapchat. As a result, a growing number are incorporating artificial intelligence (AI) in social media to better connect with potential customers. Already, just a single click can impact what notifications pop up on our social media accounts — posts, advertisements, friend suggestions, and more — because of AI products, such as recommendation engines and chatbots. In addition, AI technologies, including facial recognition and natural language processing (NLP), are helping companies improve customer service and market their products more effectively.

Expanding Social Networks Through Recommendation Engines

After friending a coworker on Facebook or following a friend on Instagram, you may notice a list of suggested people to connect with. Recommendation engines, which utilize machine learning to filter information based on user preferences, contribute to the creation of this customized list. When you engage with social media accounts and posts, the recommendation engine learns from your past activity, and then interprets patterns in your data to predict a list of accounts you could potentially interact with. Additionally, recommendation engines are involved in professional networks, such as LinkedIn, Handshake, and Meetup, to name a few.

For example, LinkedIn not only has the ability to suggest jobs to users, but it also helps companies filter out unqualified applicants by targeting specific qualifications in a candidate.

Eye-Catching User Recommendations

Have you ever started browsing YouTube and found yourself watching videos for the next two hours? Found many of the posts in your feed familiar and eye-catching? In addition to building connections and networking, recommendation engines are the mechanisms behind these personalized videos and posts. The recommendation engines collect data on the content you engage with, from pinning a picture on Pinterest to commenting on an Instagram post, and then they display the material that they anticipate you will enjoy.

Streamlining Communication with Chatbots

Too often, waiting for businesses to answer your questions takes up a large chunk of your day. Instead of listening to half an hour of music on hold over the phone or waiting for someone to call you back, many companies are using chatbots. Chatbots are pieces of software that conduct conversations via auditory or textual methods and facilitate communication between consumers and businesses because they are programmed to respond immediately to inquiries, saving time and enhancing overall customer experience, Spotify, Wall Street Journal, and Sephora already communicate with their customers through chatbots on Facebook Messenger.

In fact, as of 2018 Facebook Messenger has 300,000 active chatbots.

Efficiency and Entertainment with Image Recognition

When you post a group photo on Facebook, most of the faces in the photo are identified and automatically tagged with the help of facial recognition technology. Facial recognition requires multiple layers of neural networks, which use machine learning to identify the components of an object — in this case, facial features. Also, some social media apps, like Snapchat and LINE, offer animated lenses and filters that use facial recognition to change the appearance of users.

Currently, 80 percent of businesses make use of visual assets when marketing on social media.

As a result, more companies are working with social media platforms to increase their visual aesthetic and appeal to consumers on a personal level. For example, a company can use image recognition software to scan the photos you post and engage with and then use this information to improve their marketing. As an illustration, West Elm recently paired with Pinterest to recommend furniture through the Pinterest Style Finder tool. So, once a customer entered the URL of a Pinterest board that encapsulated their taste in furniture, they immediately received an organized collection of chairs, sofas, lamps, and more from West Elm — all tailored to their personal style.

Cropping Images Using Saliency Detection

When we look at an image, our eyes are immediately drawn to one point before we examine the rest of the picture. With the use of eye-tracker technology, which detect the pixels of a photo that people are more inclined to focus on, the saliency of certain image regions can be determined. After acquiring this data, neural networks can be trained to better predict what image components people will pay more attention to, and a photo can be cropped using knowledge distillation techniques. The idea is that auto-cropping of images can be used to help businesses determine what consumers tend to fixate on to post more engaging photos on social media. Already, Twitter has started implementing this technology to prevent images from being awkwardly cropped to enhance timeline photos.

Sentiment Analysis

Ever wonder what happens when you tweet a complaint about your espresso from Starbucks? With the help of sentiment analysis, social media software can detect the negative words in your tweet, enabling Starbucks to understand how a customer feels toward their brand. Sentiment analysis uses natural language processing (NLP) to identify positive and negative words in posts and comments on social media. With this information, businesses can consistently, quickly, and accurately respond to customer complaints.

Conclusion

In the digital age, AI is constantly transforming social media, from augmenting user experience to finding more effective ways to market products. The next time you log on to your social media accounts and upload a picture, notice an interesting advertisement, or comment on a post, keep in mind that with the help of AI, data about your activity is continuously being compiled and analyzed — and will impact what you see and engage with in the near future.

About the author:

Peyton is a rising sophomore at Wellesley College and a summer intern at Humans For AI, a non-profit focused on building a more diverse workforce for the future leveraging AI technologies. Learn more about us and join us as we embark on this journey to make a difference!