4 Ways Machine Learning & AI Are Influencing The Social Media Landscape
Social media changed the way we used to interact with each other. Social media made communication way too more accessible and made it possible to communicate without any hassle. Most of us are literally addicted to our screen and constantly scroll through social media apps aimlessly. Artificial Intelligence algorithms are a core part of social media platforms and all the digital channels and businesses storming around us.
If we look from the marketer’s perspective, social media allowed us to connect with the customers on a whole new level.
And now, with the rise of Machine Learning and its incorporation into social media, things are changing drastically. In this article, we will talk about all the changes that Machine Learning & AI brought to the social media world and how AI will affect the social media world.
Whenever you browse through Instagram, Facebook, or Youtube, you must have realized that posts and videos are recommended to you automatically on the basis of your previous actions or interests.
This is done with the help of algorithm-s powered by machine learning and artificial intelligence. One such algorithm is the KNN Algorithm that primarily makes the clusters of available data or content on the basis of shared similarities.
And with the help of these algorithms, social media apps collect different kinds of data, like the kind of content you engage with, and then display the content they anticipate you to enjoy.
Did your social media account ever get suspended because you posted something offensive? Well, let me tell you how social media channels do that! They make use of “Sentiment Analysis” and detect the text, audio, or video you put out on social media. This enables the brand to understand your sentiments towards any particular issue and lets them know how you feel.
In sentimental analysis, there is another factor called Natural Language Processing (NLP) which allows identifying positive and negative words on social media. Having this information allows social media platforms and businesses to quickly and accurately respond to user’s complaints.
Streamlining Communication with Chatbots
There were times when we used to wait long hours for business owners to respond to our queries. But nowadays, businesses can use chatbots driven by Artificial Intelligence and incorporate them into their social media accounts to react quickly to customer’s queries.
Chatbots can conduct conversations via auditory or textual methods and facilitate quick communication between businesses and consumers. They are designed to respond immediately to inquiries, save time and enhance the overall customer experience.
Related: Time series Analysis
Efficiency and Entertainment with Image Recognition
ever noticed that whenever you post a group picture on Facebook, most of the faces in the picture (if not all) are automatically identified and tagged. This is done with the help of face recognition technology. Facial recognition technology uses machine learning to identify the components of an object. Another great application of face recognition in social media apps is filters offered by apps like Snapchat and Instagram, which lets the users change their appearance.
We have come a long way in terms of technology advancement, and the pace will get double or even triple in coming years.
The next time you upload a picture on social media, watch an exciting advertisement or do any sort of engagement, keep in mind that your each and every activity and behavior data is continuously being collected and analyzed.
Senior Data Scientist and Alumnus of IIM- C (Indian Institute of Management – Kolkata) with over 25 years of professional experience Specialized in Data Science, Artificial Intelligence, and Machine Learning.
ITIL Expert certified APMG, PEOPLECERT, and EXIN Accredited Trainer for all modules of ITIL till Expert Trained over 3000+ professionals across the globe currently authoring a book on ITIL “ITIL MADE EASY”.
Conducted myriad Project management and ITIL Process consulting engagements in various organizations. Performed maturity assessment, gap analysis, and Project management process definition and end to end implementation of Project management best practices
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