We know TRP model is flawed and it doesn't give the real perspective of how many people are watching a program. One of the problems is the sample size is very small.
We follow a different approach and we try to determine the popularity of any program by youtube search.
It is very difficult to compare programs which belong to two different segments. To achieve the same,
we have decided to develop an algorithm which calculates rating based on buzz on the internet.
Further, we will do a reason-wise analysis, thus giving a buzz broader picture. The aim is to provide the marketers to find out where the money being spent on advertisement is reaching the right audience.
It will give ad managers another perspective to analyze which program is most effective on Youtube and the advertiser can directly sponsor the relevant Youtube Channels.
The preliminary comparison is done between programmes giving similar content. thus all the contents is divided into category
1) Comedy shows
2)Dance Shows
3) News
4) Reality Shows
5) Hindi Soap operas
6) Telugu Soap operas
7) Tamil Soap operas
For example, let's take a category of comedy shows:
JSON DATA -timeseries
We follow a different approach and we try to determine the popularity of any program by youtube search.
It is very difficult to compare programs which belong to two different segments. To achieve the same,
we have decided to develop an algorithm which calculates rating based on buzz on the internet.
Further, we will do a reason-wise analysis, thus giving a buzz broader picture. The aim is to provide the marketers to find out where the money being spent on advertisement is reaching the right audience.
It will give ad managers another perspective to analyze which program is most effective on Youtube and the advertiser can directly sponsor the relevant Youtube Channels.
The preliminary comparison is done between programmes giving similar content. thus all the contents is divided into category
1) Comedy shows
2)Dance Shows
3) News
4) Reality Shows
5) Hindi Soap operas
6) Telugu Soap operas
7) Tamil Soap operas
For example, let's take a category of comedy shows:
JSON DATA -timeseries
now, we make a complex program which interpolates the popularity of
