The use of big data to analyze media ratings and profitable markets is nothing new, but the terms of how that information is retrieved has not seemed to evolve much in recent memory. However, with an already nearly immeasurable amount of devices capable of streaming and downloading media content, the ratings for a TV show cannot be limited any more to simply the amount of televisions that are watching a broadcast at any one time. The amount of people streaming a show, downloading it for later viewing or mentioning it on a social media site is a vastly more complex and largely scaled data set to sift through than traditional TV ratings as we have seen up until this point. This is where Artificial Intelligence comes in, to make sense of all this data. According to http://recode.net/2015/12/16/bbc-uses-artificial-intelligence-to-track-down-new-audiences-for-sherlock/, the company which the BBC has hired to analyze viewer data for its show Sherlock, Parrot Analytics, has reported that the amount of data required to go over is on the order of several petabytes for this one show.
Image credited to recode.net; specifically this article
To better examine how large a
petabyte (PB) is, it is the equivalent of 1,000,000 gigabytes, or 1,000 terabytes
of information. And this is just for one
show, on one network. The “big four”
tech giants in the world, Google, Amazon, Microsoft and Facebook, are estimated
to hold 1,200 PBs of information altogether, across every service they offer,
according to http://www.sciencefocus.com/qa/how-many-terabytes-data-are-internet. When we start talking about the amount of
data to sift through in regards to media ratings, we start talking about data
sets that are large to the point that a human, or team of well-trained
statisticians, may never be able to comb through them all, much less actually
boil them down into useful information for an average reader to make sense of. Parrot Analytics, however, employs
artificially intelligent agents to comb through all of this information, and
low and behold, a viable, useful set of data is produced as a result.
In the article, Parrot is described
as calculating what it calls a “demand rating,” which is a measurement of the interest
in a specific media broadcast in a specific area of the world. It is the result of analyzing the total
social media mention that a show has, in a sense.
Truthfully, this is where the
analysis of data has to go, into the hands of an artificially intelligent
program to be able to make sense of it all.
In Probability and Statistics, a course taught in the Math department
(MATH 315), one of the first lessons you are taught is that a list of data that
is even as small as 20 statistics will look different to you when viewed in a
list versus when it is made into a graph.
Students and teachers alike are only able to identify patterns on data
sets when those sets are made into a visual representation. However, when that same data is presented in
a list, such as
1
1.00015
2
1.00016
3
1.00099
4
1.00127
5
1.00019
6
1.00018
7
1.00017
8
1.00003
9
1.00019
10
1.00053
11
1.00137
People will be less likely to identify patterns in that data
(here, the pattern is that it starts out low, then increases, then lowers back
to its original state, then increases again).
The end result is that these thousands of terabytes of information
result in the discovery of new markets for TV shows. In the case of Sherlock, the unlikely market
of Seoul, South Korea, proved to hold a very large number of fans for its
show. After analytics from Parrot tipped
them off that they may have a large fan base in that part of the world, the BBC
included the city in a promotional world tour, according to the news article
this writing is based on. The tour
involved being able to get a selfie in front of a Tardis replica and being able
to buy tickets to meet Benedict Cumberbatch, the actor who plays Sherlock
Holmes in the series. There were 4,000
possible tickets that could be sold, and 50,000 people physically left their
homes and lined up for them in a few minutes.
To me, this confirms the suspicion that Artificial Intelligence will be not just an
important tool to have in the years to come, but indispensable in terms of
analyzing trends. These kinds of
numbers, 2-3 PB of information for one television show, are the result of
multiple different outlets for people to express interest in a given form of
media, and as time has shown us, the available outlets to express interest tend
to increase exponentially. An article
from 2014 in the Wall Street Journal, http://www.wsj.com/articles/SB10001424052702303640604579296580892973264,
records technology giant Cisco as saying “the number of devices connected to
the Internet will swell from about 10 billion today [in 2014] to 50 billion by
2020, as wireless links spread beyond smartphones and PCs to many other kinds
of devices.” This is known as the
Internet of Things, or IoT. The data
sets which we use to analyze television shows are growing, and the data which
we can collect about cities and governments is increasing exponentially as
well. In this article, http://mic.com/articles/130132/this-high-tech-city-is-showing-the-rest-of-the-world-what-the-future-looks-like#.4EjQngQLF,
the city of Glasgow, Scotland, is mentioned to now have sensors placed under
the pavement of its streets to detect when traffic is coming, so to better time
traffic lights, for example, or to allow users of a mobile app to report
potholes in their neighborhood. Crime is
now tracked using technology, data is collected as to where more electricity is
spent, and citizens of the city can now be given notice when it might be faster
to ride a bicycle to work than drive their car.
The result of all of this information is a data set that is orders of
magnitude larger than any set of information gathered in history, and it is
growing rapidly. Search algorithms set
to find a proper time to go and fix a pothole, or agents designed to find a
good market for a TV show are now, or soon going to be, required to analyze
data sets that may soon become too large for most humans to comprehend. A more intelligent world demands more
intelligent tools to work with it, and for that, artificially intelligent
programs are not only valuable, but indispensable in terms of what kind of big
data sets they can look at, and just how they can affect our lives as a result.
I think that this in an interesting thought. The next step would be how would you be able to use this data. I think that the implications on advertising would be great. You can better target your audience.
ReplyDeleteI agree that this is interesting, but it bothers me that all this research is going towards advertising. The world is already surrounded by advertisements, and there have been psychological effects on humans. I would like to know more about analyzing big data in a hospital setting or for cars to prevent accidents. I feel like there are better outlets for producing AI to explore big data rather than tv shows. Anyone else have thoughts?
ReplyDeleteI think it's safe to say most of us would in theory prefer these better applications of A.I. and even those of us with major concerns (like me) would probably agree that there are some really fantastic and worthy possible uses. But that's not how it happens in capitalism, even if it seems like the majority of people want things a certain way. In many fields, progress is achieved by businesses through their personal, profitable applications first--even in things like science and health, often.
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