For both small businesses and large corporations, social
media is playing a key role in brand building and customer communication.
Facebook is the social networking site relevant for firms to make themselves
real for customers. Just to put things in context, the advertising revenue of
Facebook in the United States in 2018 stands up to 14.89 billion US dollars.
The advertising revenue outside the United States comes down to 18.95 billion
US dollars. Latest research reports have indicated that user generated content
on facebook drives higher engagement than ads. The amount of data that gets
added to the network increases day by day and it is a gold mine of researchers
who want to understand the intricacies of user behavior and user engagement. In
this Hackathon, we discuss one such problem where we take a step towards
understanding the highly dynamic behavior of users towards facebook posts.
The goal is to predict how many comments a user generated
posts is expected to receive in the given set of hours. We need to model the
user comments pattern over a set of variables which are provided and get to the
right number of comments for each post with minimum error possible.
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