This has been documented in a study done by Carnegie Mellon: https://www.cmu.edu/homepage/practical/2007/winter/spending-... (spoiler alert: cash 'hurts more' to spend -- credit cards 'hurt much less')
I'm sure that there is a correlation between emotion and the ability to perceive / numb pain -- so there probably (at least) an indirect correlation between emotion and buying behavior.
The mechanism is far too reductive and would only increase current problems in education. We know that a mentor for every child isn't logistically feasible but conducting these tests would just make sure we continue to work past the problem.
> It is unethical to not run tests
For instance, I have an adaptive quiz system that delivers interventions when students struggle. An intervention might be, for instance, a video for teaching fraction addition. In that case, why not compare our video with a Khan academy video teaching the same topic, and see the results?
It feels unethical to NOT use A/B tests to improve digital education. Why only apply that technology to the improvement of advertising and YouTube recommendations, vs curricular recommendations?
My reservations are primarily that it mechanizes learning and experience tells me that pedagogical measures will quickly be reduced to just test pupils that leads to the opposite of the goal, that test become more individualized for the learning requirements of the kids in question.
Another problem is that the pupils might be smart. So I wouldn't be surprised when the tests show that the best form of test is the one they just like the most or can be done with the least amount of effort, because they take being tested for granted. And while teaching math, you might also teach them to apply A/B tests on other people, including teachers of course.
> In that case, why not compare our video with a Khan academy video teaching the same topic, and see the results?
I wouldn't have any issues here. Most of the criticism is void as long as pupils get access to both resources and if there is an analysis after the A/B test and the students know about it. Would you still think it ethical, if you made it a competition between the tested groups?
Perhaps I am to cynical if I believe such measures will always be used as an excuse to delay employing more teachers and that the result of the tests will be treated as gospel, even if the failure rate is known and most classes don't provide random samples. But aside from that, I don't think this form of test is a "technology" and there can be a lot of criticism leveled against youtube and the ad industry too for that matter.
>Would you still think it ethical, if you made it a competition between the tested groups?
I do -- but it's all about framing, transparency and perceived intent.
We are planning a participatory design session between teachers, product people and edu researchers -- to design the a/b tests and generate generalizable scientific knowledge.
Might you have any further advice for us?
For example, FSU recently went up in rankings from a ~#50 public university to a #18 public university year over year over the past decade. Whatever changes they put into place are now being studied by other universities and if there’s anything novel that they’re doing, it will likely become more widespread as other universities seeking higher rankings implement new things. Or, it could be possible that the university studied the success of other universities and implemented what worked best and stopped what wasn’t. You run an a/b test when there aren’t already tens of thousands of other colleges and universities like yourself out there that you can study and learn from.
Of course, rankings DNE educational quality, but it’s one example. Another example, that may have a better correlation with educational quality (although part of the equation is the constitution of the cohort) may be bar exam pass rates for law school grads listed by law school.
Why would it be any different in webtech or advertising? Why wouldn't everyone just copy the best vs gathering empirical data?
And it may be quicker and more reliable with less risk than A/B testing in their setting. The most highly trafficked web tech companies can gather statistically significant feedback data about a change in moments. A/B testing a curriculum or educational practice could take a semester or more, and then the risks are higher — it would be a two-sided hypothesis test where the B group could not only do better, but could also do much worse, and it would reflect poorly on the institution if so. People are paying tens of thousands of dollars per seat per year for the best education they can get. Seeing how many items are in the shopping cart right on the “checkout” button doesn’t really reflect poorly on Amazon, but it could help Amazon increase conversion rates by .03%, which could mean millions of dollars at their scale, and they could also complete the test fairly quickly given their volume (in a day or so?) at a 99.7% confidence interval.
With that being said, I’m sure that smaller scale or faster turnaround time A/B tests are being ran at Uni’s.
I would bet that education is much more like Google c. 2000 rather than Google c. 2010. A general rule of thumb is that in the absence of extensive training and repeated failures, human intuition is terrible, and that any system based on people's opinions without hard data has a lot of room for optimization.
While I think this type of social contagion happens through all forms of media, social media is highly individualist so I think the effect is slightly different. I don't think it's a coincidence that the explosion of identity politics over the past ten years lines up with rise of social media. This individualism is especially obvious with post-modernist leftists - just think of how many Twitter bios start off with listing someone's gender identity, mental illnesses, ethnicity, etc. Leftist social media is more of a subculture than an actual political movement, with no discussion or debate before ideas are treated as wrongthink.
This article helped me recognize that our emotional states are also the product of that same evolutionary process. Only a few decades ago it was unheard of that people would be regularly conversing with others all over the globe from the comfort of their homes (or even more recently on their phones). Yet humans have been living on this planet and evolving to deal with the (mostly harsh) realities of life on earth for hundreds of thousands of years.
Then, it remains the question that what's different from an emotion that helps or harms people. Social networks acts in this way as a decentralised marketing tool, and totally vulnerable to non-organic manipulation.
And than mass media became the new normal. Maybe we are in this early phase with regards to social media.
Does anybody know if any scientific comparison has been done on that issue? Might be an important and useful thing!
~100 years ago Macy’s started a radio show that enabled them to quickly put out new messaging to their (mostly female) audience and see how it affected shopping behaviour pretty much “instantly” when compared to their previous paradigm of running newspaper ads. They also saved $100,000/yr doing so — the equivalent of ~$1M/year in today’s currency — demonstrating how radio had significantly tightened their feedback loop when compared to newspaper.
An artist can accomplish the same at a live show. With the artist seeing the response of a live audience (their focus group, in a way) while trying different things in real-time. This is how quite a few musical trends started.
TV, books, music, arts have all had cash flows that are responsive to decisions.
The current world brings it down to a really small reaction time (i.e. the system can change dynamically within 1s, give or take an order of magnitude). I believe there is still room for even faster feedback loops (say, when a google-glass-like device reads in real-time a person's biometrics and feeds that to a system that optimizes what the user is interacting with), and I would not be surprised if Facebook already had considered that since they deal with VR devices (Oculus).
But I guess what I’m getting at is, this isn’t anything new. The media has always been an effective social engineering tool, whether or not the social engineers at the time were aware of it. And the last few instances where faster feedback loops via more effective media helped one company get ahead didn’t spark the end of the world. Not unless newspapers were the beginning of the end. And then radio. And then video. And then TV. And then netflix and social media. And then the screens that we’ll put on behind our eyelids so that we can watch our favorite shows without opening our eyes, or whatever facebook is cooking up.
No, it doesn't. Regular physical contagions leave the victim agency in treatments, lifestyle habits that improve/worsen prognosis, etc., much as you describe for the proposed emotional contagion. And are often worse in practice than they would be in a world of ideal people because people make suboptimal use of their agency, just as you describe is the case for the proposed emotional contagion.
So, I'd say the metaphor is reasonable.
Blaming the victims will not solve the problem. This is systemic problem and only broad changes in the system can fix it.
I think that it helps if you realize that
1) People does not have access to the education that they need. We need to fix this.
2) People has many many problems to solve. So, that is why it is difficult to get focus to solve them.
In isolation the problem seems simple enough. But, taking all the factors into account we cannot expect that everybody will solve the problem by themselves. And it does not seems very efficient either. To spend millions of person/hour on this is a waste when it can be solved in a better way.
I think this is one of the most important, period-defining papers of the past ten years, and it seems like a shame how few people have read it.
This study is barely worth the paper it's printed on. Everyone in my lab was left scratching their heads that PNAS would publish such a weak result.
If you think this is important or period-defining, you haven't been paying attention to the field.
It's not important for the effect, it's important and period-defining because A: it was the first publicly-admitted instance of Facebook actually using what they had to do harm (admitted to in a way that implied they didn't realize they had done harm), and B: because it laid out how the rest of the decade would look in regard to the behavior of tech companies. What you think about the study itself isn't the interesting part; statistics/psychology aren't actually science. It's the actions and motive found within of the researchers and company that are of interest.
Well... maybe. The effect size is so weak, it barely did anything.
To give you an idea: people's hunger-levels probably influenced them about 10x more than whatever Facebook was doing.
I'm sorry, you're giving this study credit where none is due. Your conclusions are not supported by the evidence.
That's both groundbreaking and constructive, if constructive in a way that harms people who don't have Facebook stock.
It set the stage for so much of what's happening today. Acting like it's just another boring paper is baffling.
If you read the newspaper, watch TV, or read articles online, I have some bad news for you.
The actual result (people who see positive or negative messages are more likely to post the same) seems so obvious and uninteresting as not to be worth mentioning at all, though the fact that Facebook was willing to run the experiment and publish the result is perhaps more notable.
This study, which was much larger, showed that this was not the case.
From the abstract:
> When positive expressions were reduced, people produced fewer positive posts and more negative posts; when negative expressions were reduced, the opposite pattern occurred.
Well and good, when people see more positive posts, they post more positively. But then:
> This work also suggests that, [...] the observation of others’ positive experiences constitutes a positive experience for people.
What a leap into the dark that is!
This study cannot show anything about affect, only about what was measured, which is what people posted on Facebook.
I'm not defending the study in general, but the context of the research is somewhat important.
>a massive (N=689,00!)
Your critique reads like someone whose never done any research or serious statistical work. Big N's don't automatically mean the results are robust.
I'm sorry, this isn't the groundbreaking paper you want it to be.
Any way you want to cut it, these results are not to be trusted. You cannot even be sure the conclusions are true. The effect sizes are within measurement error.
Similarly, too many unregulated synaptic connections or overexcited neurons in the brain can cause seizures.
How does it bode for society if, for example, every single instance of racial animosity between people is broadcast for the whole world to see? Even if the rate of occurrence of these sorts of interactions is incredibly small, there will be many per day, driving entire segments of our society apart and causing even more such negative interactions in the future which are just fuel for the fire.
There's no serious psychology journal going to publish this kind of stuff. Why? The first problem is measurement. What is the reliability of using positive/negative words to determine positive/negative emotional state? 70%? 80%?
The effect size of this study is 0.001, which would be way way way smaller than the measurement error. LOL. What a laughable "study".
>but an unimportant journal in psychology.
This is untrue. It's comically untrue.
I was doing my PhD in cogsci when this came out and everybody was surprised that PNAS would publish such a bad study, given that we were more used to seeing things like this: https://www.pnas.org/content/pnas/106/5/1672.full.pdf and this https://www.pnas.org/content/pnas/112/2/619.full.pdf.
PNAS has an _excellent_ reputation in psychology, especially in the psychophysics and EEG/MEG crowd.
When a phenomenon with a large effect size is demonstrated with tens or hundreds of participants, everybody crows about how the sample size should have been larger.
On the other hand, when a small effect size requires millions of observations to detect, now the criticism is that the effect is too small to matter.
At any rate, this effect is small - but it is reliable. The only crappy part about this study is the ethical boundaries it crossed. In most other ways, this study was kindof amazing...