Facebook uses machine learning in several ways: 1. Automatic friend tagging suggestions and mutual friend analysis use face recognition and clustering algorithms. 2. The newsfeed arranges posts using ML to prioritize those from close friends and favorite pages. 3. Friend suggestions are made based on mutual friend circles using ML. 4. Collaborative filtering is used for recommendations like pages, groups, events and games based on what similar users engage with. 5. Sentiment analysis of comments classifies them as positive, negative or neutral emotions to provide insight.

1. machine learning in & on facebook
Sai Srinivas
15311A0568

2. In Facebook
• Automatic friend tagging suggestions: When a pic is uploaded on
facebook, a suggestion asking if you want to tag your friend in the pic
appears. This is done by Facebook's face detection and recognition
algorithms based on the advanced deep learning neural network
research project Deepface.
• Mutual friend analysis: Facebook uses the clustering algorithm to
find mutual friends.
• Newsfeed: facebook uses ML to arrange your Newsfeed too. Like
posts of close friends may come up first. Posts related to your
favourite pages come up first.
• Friend Suggestions: Machine learning is used by FB to suggest new
friends based on mutual friend circles.

6. • CF[Collaborative Filtering] is a recommender systems
technique that helps people discover items that are most
relevant to them. At Facebook, this might include pages,
groups, events, games, and more. CF is based on the idea that
the best recommendations come from people who have similar
tastes. In other words, it uses historical item ratings of like-
minded people to predict how someone would rate an item.

8. Ads on facebook
• The process of placing an ad on News Feed is a complicated
dance. Facebook has to decide not only which ad to show to its
users, but when to show it to them. There isn't a dedicated
"slot," so to speak, for an ad in News Feed, so the team must
time the ads based what the user is doing on Facebook at that
given moment.

9. On Facebook
Business people use facebook data to:
* Promote relevant products
* Grow brand awareness
* Get qualified leads
* Close the loop

10. Sentiment Analysis
• Sentiment Analysis can be used to automatically detect
emotions, speculations, evaluations and opinions in the content
that people write. The sentiment analysis tool extracts data from
the comments on a post, cleanses the data and processes it to
give us an analysis in the form of a graph that classifies all the
comments into polarity and sentiments. This provides insight
into comments by classifying them into three polarities
(positive, negative & neutral) and into six different emotions
(anger, disgust, fear, joy, sadness, surprise). Most of the
algorithms for sentiment analysis are based on a classifier

11. Bayes' Theorem
p(Ck)= p (occurrence of class) [prior]
p(x)= p (instance of word) [likelihood]

12. • Its classifications regarding the decisions are surprisingly accurate.
The above function returns an object of class (data.frame) with seven
columns (anger, disgust, fear, joy, sadness, surprise and best_fit
category). This best_fit is the most likely sentiment category among
the six emotionsfor a given content item. Similarly, we will classify
polarity in the text and combine the emotions of all the comments. In
simple words the approach is, if a piece of content has more positive
keywords than negative keywords, it’s a positive content; if it has
more negative keywords than positive keywords, it’s a negative
content.

13. • After the classification, we fetch the “best_fit” category for
analysis. When all the data is cleansed and processed we enter
the next phase: strategic representation of data. In this phase the
processed data is subjected to a function named ‘ggplot()’,
which plots the distribution of emotions (anger, disgust, fear,
joy, sadness, surprise). Similarly, we can plot the distribution of
polarity (positive, negative and neutral).

15. Deep Facebook Analysis for business
*Analyze Your Competitors
*Gather Your Data
*Analyze Your Facebook Page Data
*Analyze Your Facebook Posts
*Ask Yourself the Right Questions
*What to Do After Checking Page & Post Data

23. Conclusion
• Facebook use our data to provide better services to us and
business people use this platform to manufacture the products
based on people's interest which is a good sign.

24. References
*https://sproutsocial.com.
*https://facebook.com/full_data_use_policy.
*https://en-gb.facebook.com/business