Role, application and use cases of ai-ml in next-gen social networks

1. MACHINE LEARNING AND ARTIFICIAL
INTELLIGENCE FOR NEXT GENERATION
Presented By-
Prachi Gupta

2. • What is AI?
• Social Media Marketing
• Applications of AI in Social Network
• Roles of Artificial intelligence-Machine
Learning
• Use-Cases of Artificial intelligence-
Machine Learning
• Next-generation, artificial intelligence
and machine learning

3. • The study of computer systems that
attempt to model and apply the
intelligence of the human mind.
• A branch of computer science dealing
with the simulation of intelligent
behavior in computers.
• The capability of a machine to imitate
intelligent human behavior.
What isAI?

4. • Social media marketing is the use of social media platforms to
connect with your audience to build your brand, increase sales, and
drive website traffic. This involves publishing great content on your
social media profiles, listening to and engaging your followers,
analyzing your results, and running social media advertisements.
• The major social media platforms (at the moment) are Facebook,
Instagram, Twitter, LinkedIn, Pinterest, YouTube, and Snapchat.
• Social media marketing is about analyzing customer data which is
humongous and complex. You should hit hard on repetitive work
and should evolve marketing with the help of Artificial intelligence.
SOCIAL MEDIA MARKETING

5. Applications of AI in Social Network

6. Advertising
• Advertising platforms give us tons of data to work with,
including measurable impressions, click-through rates,
bid levels, demographics, and more.
• Humans certainly have the ability to produce good
advertising, measure that advertising, and improve ads
based on what they learn. But, digital advertising across
search, content, and social media channels, gives us an
almost unlimited ability to generate data on what works
and what doesn't.
•
Artificial intelligence isn’t just creating ads, though
commercially available platforms exist that use AI to
create ads without human involvement.

7. Content Curation
• Content curation is about finding high-quality relevant
content from external sources and promoting it to help
build your authority and engagement. Similar to content
creation, curation can be automated using AI and machine
learning.
• With this type of tool, you can engage in data-driven
content marketing at scale with a minimum of effort. I’m
sure you’d like to generate more and better marketing
content in less time

8. Image Recognition
Image recognition is a computer vision technique that
allows machines to interpret and categorize what they
“see” in images or videos. Often referred to as “image
classification” or “image labeling”, this core task is a
foundational component in solving many computer
vision-based machine learning problems.
Image recognition is one of the image processing stages.
Those specific features which we mentioned include
people, places, buildings, actions, logos and other possible
variables in the images. Therefore, image recognition is a
process of identifying and detecting an object in a digital
image, and one of the uses of computer vision. Sometimes
it is also called image classification, and it is applied in
more and more industries. One of them is e-commerce.

9. Increased Conversion Rate
• An intelligent chatbot that actually uses AI can help you in a
fast and efficient way to provide better customer support or
makes the sale process much shorter.
• Chatbots existed long before; the same applies to google
translators or digital assistants. But the quality of their
performance left much to be desired before using deep
learning methods.
• Speech and face recognition, image classification, and natural
language processing helped these products take really great
leaps forward.

10. Roles of Artificial intelligence-
Machine Learning
There are many features in social media that usages Artificial
Intelligence. like for example:
1. Your face filters use artificial intelligence to detect the nose,
eye, and lips in order to construct the filter.
2. The Auto tag feature was made possible only because of the
face recognition capability of AI.

11. Use-Cases of Artificial intelligence-
Machine Learning

12. Sentiment Analysis
• It can also be a sentiment analysis that is extremely
useful in social media monitoring as it allows us to
gain an overview of the wider public opinion behind
certain topics essential part of your market research
and customer service approach.
• Not only can you see what people think of your own
products or services, but you can also see what they
think about your competitors too.
• The overall customer experience of your users can be
revealed quickly with sentiment analysis, but it can
get far more granular too.

13. • Often regarded as the “darling of the media”, chatbots
(or bots) are currently one of the most popular AI
technologies.
• Usually built with an AI-Powered Chatbot Platform,
these virtual assistants are deployed on messaging apps
like Facebook Messenger, Skype, Skype For Business, etc.
to converse with end-users.
• Users can send a question in natural language and the
bot will instantly reply with the relevant answer via a
chat interface. These bots can also learn from the ongoing
conversations and deliver personalized responses to each
user
Chatbots

14. Next-generation, artificial intelligence
and machine learning
We’ve seen that current A.I. and machine learning technologies
suffer from various limits. Most importantly, they lack the
capacity for:
• Personalization: To successfully protect and serve customers,
employees, and audiences we must know them by their
unique and individual behavior over time and not by static,
generic categorization.
• Adaptability: Relying on models based only on historical
data or expert rules are inefficient as new trends and
behaviors arise daily.
• Self-learning: An intelligent system should learn overtime
from every activity associated with each specific entity.