On the 17 of September 2014 the US streaming portal „Netflix“ startet its online service in Austria. Netflix is the leading streaming service worldwide „with more than 44 million streaming members in over 40 countries enjoying more than one billion hours of TV shows and movies per month“ (Netflix 2013: 1). Thereby one of the key strengths of Netflix is collecting big data. By that it uses a personalized algorithm, „which recommends other shows to watch based on what the user has seen“ (Nippes 2014: n.s.). Critical voices claim that through that the creative process of discovering and liking a series gets lost, because the algorithm offers the user programmes it thinks they will like (cf. Leonard 2013: n.s.). Keeping that in mind Netflix has a great power to promote series that are produced by themselves (for example „House of Cards“) or even other shows from other providers.
For this reason in this paper I will discuss how user information and big data is used to manipulate users watching suggestions and try to expose what it implies of the future of streaming portals. Therefore I will begin with a short description of streaming portals in general. Then I will continue with the concept of big data and it’s underlaying principles. After that I will briefly introduce the US streaming portal Netflix. Finally, I will talk about how Netflix manipulates users suggestions and how the possible future of streaming portals will look like.
References
Leonard, Andrew. 2013. „How Netflix is turning viewers into puppets“. http://www.salon.com/2013/02/01/how_netflix_is_turning_viewers_into_puppets/ (accessed 26 September 2014).
Nippes, Daniel. 2014. „Netflix’s Big Data Architecture“. http://dataconomy.com/netflix-big-data-architecture/ (accessed 26 September 2014).
Netflix. 2013. „Netflix, Inc.“. http://files.shareholder.com/downloads/NFLX/3504957457x0x748407/76a245dc-3314-401c-baba-ed229ca9145a/NFLX_AR.PDF (accessed 26 September 2014).
Ohlhorst, Frank. 2013. „Big data analytics: turning big data into money“. N.J.: Wiley, cop.
By Julia Pechmann
Interesting topic! Very relevant to most people in the future as well. Try to elaborate on the consequences of the use of the algorithm for presenting sugestions, not only for the end-users but also for the companies and the content providers. Note that you can split up the content providers in mainly two groups; the one related to the platform and the ones who are ‘independent’. Furthermore if you’re explaining about Big Data this infographic of IBM might help. http://www.ibmbigdatahub.com/sites/default/files/infographic_file/4-Vs-of-big-data.jpg The concept of the 4V’s to describe big data are widely accepted I think and if you discuss it properly, it helps the reader to gain insight in the properties of Big Data and the challenges it brings (also related to information management). Good luck with writing your draft and final paper!
Arthur Verkerke
You have chosen a very interesting topic! Especially our generation uses streaming services like Netflix and I am very curious about the observations you will make. I agree with Arthur, that it might be a good idea to differentiate between the impacts of the Algorithm on the end consumer as well as the impacts on content providers. Further, you have presented a very clear structured synopsis and I am looking forward to read your draft.
BR,
Frederik
I agree with Arthur and Frederik, it´s a really interesting topic.
The structure of your paper is clear and understandable.
I would also be interested in the questions of whether this algorithm one is a kind of “distortion of competition” as their own Netflix series advertise courted more than others. What do you think?
I wish you much success in writing your papers!
This is a very relevant topic of the larger discussion on how out data is being used. I think you would benefit from it if you separate the problem into two parts: 1. our data is being collected 2. we are recommended things we already might be interested in. The first part can still be a problem even if the second part isn’t necessarily one.
Obviously there is something suspect in the fact that a commercial entity is collecting our data but is the recommendation of things relevant to our interests truly suspect? Granted the recommendation did come from the data that was collected but is it truly accurate to call it manipulation? Technically commercials and advertisements are trying to convince us of different thing as well but should we really understand them as manipulation? Commercials I would consider benign even if it would be considered manipulation of some sort. You have to consider that we can always also ignore advertisments. I think you have to acknowledge in your paper that a recommendation in itself does not have to be bad or even “manipulative” and that it can even be considered helpful. Recommendations could also be seen as directing people to the content that is already relevant to their interest even though they were a result of the ethically questionable collection of people’s viewing habits.
Great! There is not too much stuff written on this topic. Try not to be overtly negative (but be critical of course, that’s good!) and focus on Netflix. Going too far to streaming portals in general might distract you a bit too far.