AI in social media: how algorithms redefine online spaces

AI in social media: how algorithms redefine online spaces

April 25, 2022

Andrea Di Stefano

Technology Research Analyst

We live in a society where personal development or building solid and fruitful human relations have always depended on so-called social intelligence. Making friends, developing new passions, or finding a job are mostly driven by our ability to manage complex social situations.

But is that still the case? Partially yes and always will be. Nowadays, however, other underlying forces stand alongside interpersonal skills. One of them is technology, especially social media and all those artificial intelligence algorithms ruling over their mechanisms.

The book that inspired you to take up a new hobby? Maybe you read its review in an online community and bought it. And what about the company you work for? You may have spotted their job opening on a professional networking platform. In each of these situations, it was probably not you who found that content, but the content that "found you". All these wonderful things are happening because of social media’s increasing reliance on artificial intelligence consultancy. So let's delve into this fascinating topic and find out why technology companies put major investments into AI services and how this advanced technology impacts social media and our lives.

The role of AI in social media

Social media's impact encompasses job careers, sales trends, and even the way we perceive the world, including our hopes, ideas, and beliefs. Most of their success in doing so comes from their ability to efficiently connect people, organizations, and digital content or products, making them a valuable tool both from a purely social and business point of view. But how?

AI in social media is the force powering such capabilities, particularly its sub-branches known as machine learning and deep learning, and other AI-related cognitive technologies such as natural language processing (NLP) and computer vision. These disciplines are paving the way to an increasing range of applications in the social media sphere, which include:

  • Assessing user sentiment to identify major cultural, political, or market trends.
  • Customizing user experience based on preferences, interests, and attitudes.
  • Supporting or even automating marketing campaigns and media content authoring.
  • Providing 24/7 customer support via social media chatbots and virtual assistants.
  • Detecting and removing harmful content with efficient moderation tools.

Needless to say, the leading role played by artificial intelligence in unlocking these features influences and is in turn influenced by the growing investments of social media enterprises and related industries in AI services and development.

In this regard, Verified Market Research's 2022 AI In Social Media Market study predicted that the global AI market in the social media field is set to grow from $0.74 billion in 2020 to $6.12 billion by 2028. Similar estimates have been reported by Mordor Intelligence: based on their 2021 AI in social media market research, this market is expected to grow from $815.33 million in 2020 to $3,714.89 million by 2026 at a CAGR of 28.77%.

AI in social media market forecast, 2020-2026

The aforementioned reports provided further insights into the reasons behind this skyrocketing growth. Among such key drivers, analysts identified:

  • Ecommerce companies' interest in targeted advertising and personalized product recommendations on social media.
  • The increasing adoption of AI-powered chatbots, especially banking assistants in the BFSI sector.
  • The mass digitalization experienced by developing countries (including smart homes and smart cities) and resulting in a massive stream of information to fuel data analytics.

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3 AI use cases for social media

We previously mentioned some of the key AI trends and use cases defining the way we approach and leverage social media. Let's delve into this topic, starting with the role of AI-powered systems in providing a fully customized user experience.

1. Tailored content delivery

When we said that in social media it is not the users who find the content but the content that finds them, we meant it. But this is probably for the best, we may add, since social media is a  boundless realm and without any  kind of guidance, we would get lost among a sprawling, virtually unlimited offer of digital resources, products, and services. Artificial intelligence, specifically in the form of machine learning algorithms, represents a beacon leading us right towards the content we actually need.

Nowadays, any major social media platform relies on machine learning-based recommendation systems to segment users based on their profile data and behavioral patterns (shares, likes, comments, purchase and browsing history, etc.) and target them with customized content suggestions. LinkedIn, for example, uses a similar engine to provide job recommendations, suggest potential connections, sort relevant posts at the top of each user's newsfeed, and offer specific online courses on its eLearning platform.

LinkedIn Learning's course recommendation system

Another trick to direct social media users towards the content they might be interested in is to implement smart search engines. Are you looking for a music video on YouTube but you don't remember the exact name of the song or its singer and you misspell it or start typing random words vaguely relating to that content?

It's likely that a smart search engine, powered by machine learning and natural language processing, will understand what you meant by considering several contextual parameters, such as common keywords and synonyms, search trends, or your browsing habits, and provide customized search suggestions (similar to Google's autocomplete feature).

Machine learning-based smart search engine

Fun fact: as an experiment we typed "stupid Italian philosopher" while looking for the latest statement from an intellectual who let us put it mildly, we don't really appreciate, and it worked!

2. Marketing automation

Unsurprisingly, the possibilities unlocked by AI in terms of user segmentation and content customization not only give a significant boost to social media platforms' performance, revenues, and user experience, but also become a godsend for marketing and sales.

Indeed, the combination of artificial intelligence and social media provides everything necessary to identify the needs and desires of the user base through effective market analysis: the immense amount of personal data shared on such platforms, the cognitive technologies (computer vision and NLP) to harvest information from textual or visual content, and the solid computational power of machine learning systems to process it and identify recurring patterns or trends.

This synergy (clearly visible also in implementations of machine learning in ecommerce) reflects in the constant growth registered both in social media-related digital marketing channels and the adoption of AI in this field, as shown by Salesforce in its 2020 Sixth State of Marketing Report.

AI and channel trends in digital marketing, 2018-2020

How does this affect marketers' job on the ground? Basically, AI-powered data analytics and social media intelligence can be used to:

  • Understand the type of content that social media users are likely to appreciate, share, or interact with based on their archetype.
  • Assess user sentiment, namely their perception of a certain brand, product, or general topic.
  • Combine user data on a larger scale to shed light on major market trends and purchase patterns.
  • Identify new potential marketing channels and promising market audiences to target.
  • Fine-tune marketing campaigns (in terms of publication timing, hashtags, visuals, and more) to increase brand reputation and generate conversions.
  • Monitor competitors’ social media strategies to replicate their strengths and avoid their mistakes.

To perform such tasks, online retailers and service providers can count on social media platforms’ embedded analytical and content recommendation features, which allow marketers to run advertising campaigns targeting specific demographic and behavioral segments. In addition, they can complement their market analyzes with custom software solutions.

Example of social media sentiment analysis dashboard

However, the role of AI in social media marketing is not limited to data analytics, as it has also proved essential in automating several tasks and providing assistance to customers.

  • Social media chatbots: The growing importance of social media in marketing and sales has also resulted in an increasing number of interactions taking place in their instant messaging applications. To mitigate this growing workload, various platforms have implemented AI-powered chatbots with advanced NLP capabilities, which allow businesses to communicate with customers round the clock. These include Facebook, which launched its Messenger bots in 2016. Chatbots can assist users in a variety of cases, such as placing orders, finding products, or making reservations.
  • AI-generated content: Businesses can also leverage AI and natural language processing to speed up social media content authoring and distribution. Nowadays, several tools for automatic content creation allow marketers, as well as journalists and other mass media professionals, to generate brief comments, reports, stories, and analyses with proper hashtags or links and publish them on several platforms to enhance social media engagement. For example, the UK Press Association adopted a similar solution to write thousands of local news stories each month.

3. Toxic content recognition

The legendary Italian novelist Umberto Eco once said that "Social media gives freedom of speech to legions of idiots who previously only spoke at the bar after a glass of wine, without hurting the community". Perhaps Eco was a tad too judgemental, but social media's ability to dramatically amplify the spread of potentially harmful content is a problem that should not be underestimated.

To contain this deluge of toxic content and keep trolls at bay, many social media platforms have been equipped with AI-powered systems complementing human fact-checkers, professional moderators, and user reports with powerful machine learning algorithms. These tools can scan millions of images via computer vision to identify violent visual content, while monitoring comments or posts through NLP to spot signs of hate speech, fake news, spam, and cyberbullying.

Content moderation workflow

The most advanced content moderation systems can even detect fake accounts based on the analysis of their behavioral patterns, including Facebook’s Deep Entity Classification (DEC), which erased 1.7 billion fake accounts in the fourth quarter of 2021 alone.

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AI in social media: risks and precautions

We live in an era where social fabric and social media intersect like threads in the texture of a Persian carpet. While they may not be as elegant, these social aspects are certainly as precious as that famous handmade item. Every day, we donate our time, our attention, our data to social networks, which give us back opportunities, new friendships, and a (not necessarily truthful) overview of the world surrounding us.

The advantages of this symbiosis are many, but several controversial issues may be far from being resolved. One of them is the central role of AI, which became the fundament of the entire social media architecture but is also well known to be an extremely data-hungry technology and therefore prone to be abused.

Many of you probably remember the infamous Facebook-Cambridge Analytica scandal, which proved how personal data could be weaponized by insidious powers and how the AI algorithms ruling over the platform’s functioning could foster misinformation and hate speech instead of mitigating them. The lesson we can draw from these events is that AI is an amazing tool, but the benefits that come with it depend mostly on the way we implement it in various aspects of our society, including social media.

In recent years, fortunately, public opinion and legislators have paid increasing attention to this topic, leading to the creation of greater safeguards in terms of data protection, such as the GDPR. So, the general trend seems to be positive. This might ensure that similar social media credibility crises (including those embarrassing interactions between Zuckerberg and politicians during a Senate hearing) do not recur in the future.