The brazilian student G.N. has send me his first Movie Pulse result: “Life” of Daniel Espinosa. This movie has been a solid outer space science fiction to me, whose crew experience felt quite intense. I’ve literally been part of their crew.
I reject the “Alien-alike” bashing of this movie. It had a serious impact to me – encounter a life form of this aftermath combined with it’s inconspicuous appearance.
But this is it so far on discussing the (subjective) quality – I tend to show some nice similarities across oceans, borders and time. G.N. and me have had some strong identical reactions while watching this movie. I made again a simple image multiplication and only shifted the base line. The first two thirds are somewhat ok, but the reactions at the last 30/40 minutes are almost identical. Shifting the base line for each third would have unfold more similarities even within the first hour.
These are the original graphs drawn by Movie Pulse.
Wow, this has been a while. Silence means not inactivity. So I’d like to give you some updates right now. I will start with this great movie “Passengers” by the Norwegian Morten Tyldum (director) and Jon Spaihts (writer) from 2016. To my extend this is a new landmark for future design and an example of dedicated craftsmanship in script writing. A limited cast with a great dilemma in existential scale. It has been a pleasure to be a part time space (and time) traveller while watching this movie with its superior production design. Guy Hendrix Dyas work is nominated for the Oscar 2017. He better be!
I’ve been accompanied by 15 students of mine – they’ve been willing to give me their heart rate in exchange for the ticket. It was a kind of semester goodby as well. Their results are not yet evaluated. The raw data looks very mixed, as always.
But because I’ve seen the movie twice, I’ve been curious to compare my first and second visit of the same movie. I felt very strong body reactions because of certain story incidents, as well as from the brillant sound. Did I mentioned the audio? Wow, terrific! I found an insight of the work of Will Files – one of the gifted audio folks involved.
A short look at both graphs made available through my app Movie Pulse obviously confirmed my presumption. But that even the high and low peaks at the end match 100% is definitely by chance. I combined both graphs for better comparison.
Since I do not yet have the movie available on DVD or Bluray I can only guess what happened after 1 hour. I am pretty sure that this has been caused by a simply two line dialogue, because at the 2nd screening I knew instantly that these en passant spoken words will have serious consequences. As I write these lines: what if not? Let’s see later, if the movie is available. Come on, it’s an assumption, can be proven wrong…
Jim: There’s no secrets between us.
Arthur: Is that the case?
Because I have access to the raw data of the recordings on my research devices (which is not [yet] available at the official app at iTunes, because of privacy rules), I can get my hands on the data curves. I made two graphs, comparing both recordings. As always the data is now basis 0 at the average heart rate and normalized.
There are a bunch of movies with a horseload of data waiting to be analyzed and evaluated. Among them the heart rates of 15 people watching this movie. Let’s see if I can find some more conformity comparing those, rather than my own visits. Dr. André Weinreich and me are almost done with the sessions in this semester. I will give you a follow up what happened the last months.
We had a long awaited trip to the cinema with our two boys, age 6 the little and the older one became 8 years old just recently. They have watched so many Angry Birds Shorts and now wanted to see the feature movie. When I asked them why, they could not really state more than “it’s fun”. I’ve read a very short review stating it’s a sequence of gags only. Not a good starting point for parents.
But to make an ease start: we’ve had fun watching it. Recording the pulses of all family members had brought some prove that these kind of movies are build on two major layers (if we disregard the fact that we four are not a qualified test screening quantity).
I won’t go into detail on the movie itself. It’s a merely simple world and characters, compared to “Zootopia” for example. But the richness of references to contemporary and history of media has a certain quality. We, the parents, had often laughed out loud: Terence can be seen as a revenant of Chief Bromden from “One Flew Over the Cuckoo’s Nest” and you can meet the female twins of “Shining” as well as you can party with Daft Punk. Not to mention that Rick Astley’s “Never Gonna Give You Up” will be played at a central moment for the (former) hero Mighty Eagle. And the main character Red has a interesting personality and a goal; presumably this movie has a story after all.
depicts the time children and parents reacted different while watching the movieThe following steps will explain how this result has been achieved. If you’re not familiar with the workflow I developed so far, I recommend reading the “Citizen Kane” post first, because I’d like to refer to some steps with not going into detail again.
All of the four records of the family members are changed to relative values, based on their single average. Parents records have a warm color, the records of the children are shown in cold tones.
Higher values show greater discrepancy. Dark grey depict areas of less than average aberration, which means the majority of viewers tend to have the same reactions, either above or below their main average.
The red line shows the moments of the film when the complete family has reacted in the same manner: all four have had either a raised pulse above zero, or had have a calm pulse below zero. The amount of accordance over time is 17,6%. But I now start a little clustering and interpretation.
As I stated in the beginning: I refer to the same procedure I developed for “Citizen Kane”: besides the finding of 100% accordance, I am looking for the areas of conformity of the majority of viewers (3 out of 4). This shows a greater pattern of resemblance over time: a high result of 68%!
But this time I will try something new: I’d like to match the differences of the children’s outcome with those of the parents!
The results are divided into the subcategories “Parents” and “Childs” and their results are computed separately. This proofed the idea that watching “The Angry Birds Movie” triggered both groups in different ways.
·100% accordance of the parents ·100% accordance of the children ·discrepancy of parents vs. childrenThe green row is the result we’ve had in different styles beforehand: 100% accordance (17,6 %) of all family members. Grey is used to mark the timespan when both parents reacted similar (astonishing 57,3%), blue shows the conformity of both boys (an even higher result of 58,8%) and finally red discloses disparity between the parents and children’s reactions (50,4%).
We are one step closer to our general aim. For identifying structures within movies we analyze the heart rate of the viewers with our Movie Pulse app. Because of a generous support we’re now able to record up to 5 viewers in parallel! For a first start with multiple Apple Watches we’ve had four volunteers watching “Citizen Kane”. All Watches are paired to a single iPhone 5 and committed their data without any hassle. The data shows no gaps, missing periods of recording. Only a small exception of being perfect: one record stopped prior the end of the movie. Perhaps the user inadvertently pressed the stop-button. Therefore the last 13 minutes are not having the base of 4 recordings and are less significant.
Having watched “Citizen Kane” is an important requirement in terms of understanding the history of cinema. That motion pictures are able to condense what went wrong in an entire single life with a single ordinary object – this really strikes me every time I see this movie. I don’t want to go into details here. “Rosebud” is all I have to cite.
If we now have a look onto the raw data of our Movie Pulse volunteers – my first reaction has probably been the same than yours: Am I on the right track? For heaven’s sake, how could this mess matter in any meaning?
They all must have seen another movie or the whole Movie Pulse enchilada is for the birds. Wait. The data needed some nurture.
Absolute figures are nonsense
We need to have a look at each recording individually. Each person has his/her own resting heart rate. We don’t know this rate, but we can calculate the overall average for the movie records of this person. This figure along with the minimum and maximum pulse in this period of time is the starting point of all our computations. In the Movie Pulse app there is a far more sophisticated algorithm which computes not only the overall average, but the average changing within a specific time frame. This gives the nice up and down trend line. Having here the plain average will be sufficient for now.
Adjust the base
What formerly has been the average will now serve as the base – zero null. The numbers of units from average to the lowest will represent the minimum range of units the person has reached. The maximum units are defined the same way above zero. Instead of having a heart rate, we deal with a range of units at a base of zero – the threshold of maximum and minimum our test person has reached at a particular time within the movie.
Amount of deviation
A first attempt is to identify the amount of difference at each recording time. Let’s say at time 0:32:12 person 1 has a value of 4, person 2 a value of 6, person 3 a value of 7 and person 4 a value of minus 4. Three people are above their individual average and one person is below it. The deviation is 4,43…. somehow complicated, therefore computers come in very handy. Two more simple examples: p1 value 1, p2 value 1, p3 value 1 and p4 value 2 will have a deviation of 0,5. Yes 1,1,1,1 will gain 0,0 – no difference at all. Low deviation will mean great conformity – which, in our analysis, is the biggest proof of having viewers responding similar.
To make this graph more readable I added a simple TRUE value for those recordings which have a small deviation (average or below), which is represented by the darker gray. This is a first hint for periods of time which have gained equal reactions.
Direction is all we need
But there is one problem: How about the differences the test users have in terms of range of threshold? Of course, according to my theory, a very high or low value will state either high attention or intense state of being calm. But this is the peak we might come closer soon; for now it’s more elementary and useful at which moments the viewers responded in the same way, the same direction!
I came to the conclusion that having an overall average of all four users might not sufficient and will alter the data in a wrong way: Imagine one person reacting completely different. With pure math average his or her data will be taken into account nevertheless it might be completely different than the majority. This is what we’re after: majority.
For this reason I computed the graph depicting the average raise or descent of A) all four test persons B) of the majority of 75% of the test persons which is shown in red and green. Therefore A) is a subset of B) and is marked in black on this image (white in the video).
Again the movie is boiled down into 2 minutes excepts, placed beside each other; one row representing 30 minutes of the movie.
Those 100% and 75% conformity results have been used in the “Citizen Kane in 2 minutes” movie. The overlay of green and red color is applied at the same rules as the prior published “Metropolis in 2 minutes”: high units above the average will tint the image in red, low units in green. This time the color is multiplied with the image, not overlayed.
The video takes the average threshold of the majority (75%) into account – again the image becomes tinted in green and red. Additionally the 100% subset of all four test users has been included as well. To distinguish both data visually, a hint for the 100% subset has been added in white. If one image shows a white frame: this means all viewers have reacted the same way, not only the majority. The graph below the timeline shows this subset in white as well.
Please remember that this first multiple recording unfortunately is not complete approx. 13 minutes prior the movie ended. So “n” has changed from four to three persons at 1:39:12. There is always room for improvement. Any sugestions are welcome too!
Convincing my 6 year old son to wear my Apple Watch is easy, because he and his brother love it, but it has been a challenge to get it properly mounted at his arm. The mother has not been around and he did not yet know what Gaffa-Tape stands for.
My sons have seen the trailer with Flash over and over again. And finally here we are, in “Zootopia”. I had have no big expectations and seeing the trailer so many times changed my mood from “this must be funny” to “I got it”. Once more now I am so thankful not to have seen anything else of the film – letting me know the identity of Mr. Big, among so many other surprises, would have spoiled the enjoyment. We burst out laughing so many times.
At the other hand both of my sons are not yet very familiar with suspense and drama. And seeing the world of movies through the eyes of a 6 year old, will definitely change your perspective on cinema. I remember proudly presenting them “An American Tail” aka “Feivel, der Mauswanderer” as a funny animated highlight. After 7 Minutes or so I had to stop the movie because I had forgotten it starts with a genocide – mouses are convicted by cats and their homes are looted and burned.
So fear and getting the creeps has been part of “Zootopia” as well, in terms of my sons. The younger told me, tho older won’t tell, but silently gives consent. These reactions can clearly be identified by the large red areas and the constantly increasing heart rate at the whole length of the movie. Too bad that we had somehow a silent part in the middle – probably having the watch not that properly attached. I planned not to use this recording because of the missing middle part – until Alexander, a student of mine, has send his result of the same movie.
If you look at both graphs independently, you would not identify any resemblance at first glance.
He started at the studio fanfare of Disney as we did, but he waited until the very end of the credits. We left at the beginning of them, what explains the different lengths. So I made an overlay and repositioned the graphs with the 1/2 hour scale units to properly match in time. The heart rates are so different concerning the trend line, but while trying to find similarities on comparing red and green areas, I discovered that some of the peaks every 1/2 hour are very close together. One is exactly at the same minute, one differs only a single minute and two are at least only two minutes apart.
These two recordings bear strong resemblance – probably by chance. I am more and more motivated and curious to compare a bigger quantity of Movie Pulses of the same movie.
I have been persuaded by friends of mine – this movie was not my choice. The trailer already gave me the feeling that this would be a long and boring time in cinema. And I should go with my instincts.
But after having recently so many movies I was fond of – I have to admit it was somehow curiosity. If things go that bad: How will the Movie Pulse look like, of a film I don’t like? According to my feelings I went near sleeping pulse after the opulent and impressive introduction of the characters and the setting. Only the visuals by Robert Richardson kept my attention, I was basically trying not to be disturbed by the loose tongues of the cast. I slightly had the impression having a bath tube shape of heart rate: great expectations, low outcome in the middle and an effectuated raise at the end.
Btw. What did Tarantino say to Tim Roth? Look at Christoph Waltz characters in my recent movies and copy what you like? But please don’t be that good?
If we now have a look at the graph, one must say I was somehow wrong, but not completely. There is a longer increase time at the beginning, a longer decrease time at the end and you can see the valley in the middle, which is not that extraordinary as expected. But the “waves”, the trend line my heart rate performs, could be interpreted as turning points: having a raise until approx. 0:47 – then going down until 1:30 to catch my attention up to 2:20. The “Schlachteplatte” at the end could not attract interest for the rest of the movie. 2 hours and about 45 minutes of my lifetime I could have spend with movies which really matter. Again: the DOP helped making this bearable.
This is a single, subjective and yes, prejudiced interpretation, which points out the future of Movie Pulse: there must be a solution to anonymously compare graphs of other people which have seen the same movie. A solution to render an average graph of multiple sources and compare your own with that.
How would a Tarantino enthusiast’s graph look like, in opposite?
Here comes a first result to compare the heart rate of two different people watching the same movie. Both persons have seen the movie in different locations and at different times (Person 1 & 2).
At first I put graph one onto the other – regardless of the absolute heart rate, which resulted in a centered position in y, which is the pulse (Person 1 +2 Overlay). Because of the visual confusing outcome I decided to identify similarities via simple color multiplication (Similarities [Overlapping]).
This is my theory what this result can tell: In those regions which have overlapping color (red + red or green + green) both persons have had the same kind of pulse: either above the trend line (red) or below (green). This means both persons have been emotionally touched in the same manner. So the bars in grey depict those time frames, where both individuals have been responded similar – although they have seen the movie in different locations and at different day time (and of course at different dates).
Person 1 fails keeping attention after 30 minutes – it’s me, folks and this is why: I went to the cinema in the afternoon, when I usually have my energy drop.
A colleague of mine watched as well “Star Wars: The Force Awakens”. She used the watch and app as well, and so far I can tell – there are differences (besides the fact she’s not seen the movie in an energy drop time of the day).
Different person and heart rate
This looks more “spectacular” to me, which has been the reason to use this pulse for the default movie – not mine.