Social Media: Bad for our Brains?

Are the science papers that scientists are publishing getting harder to understand? Chris Smith heard how one scientist, William Thompson, thinks they are…

William - We were four PhD students frustrated about reading different scientific texts. We had journal clubs together and there was particularly one person that we were reading repeatedly that we thought was hard to read. We joked originally, has this person always been hard to read or is this something which is developing as the ideas developed?

We realised we could quantify this, and as soon as we realised we could quantify it for one person, we realised we could apply the same tools and get a much larger corpus, which was over 700,000 scientific abstracts. We made a list of 123 highly cited journals from 12 different fields, then we tried to quantify the readability. So, for example, the number of words per sentence and the number of syllables per words and tried to make an estimate about how hard it is to read.

Chris - What time frame did this span?

William - The earliest article was 1881, but most of the scientific literature started to appear around 1960 that we could get our hands on and then up to 2015.

Chris - When you run the text from those abstracts through the analysers and ask it to score the language that’s being used, what trend emerges?

William - We found a large downward trend in readability, and that means that texts are getting harder to read now compared to previously. We were surprised at how strong the trend was.

Chris - You looked at a whole raft of different journals which means that you could consider different scientific disciplines, so are any disciplines particularly prone to this or is it that all scientists across the board now have a tendency to over complexification and use of long multisyllabic words where simple terms might actually be feasible instead?

William - I think the important take-home message was that all the fields we looked at were getting worse. There were some differences, for example, clinical medicine was the least worst, and molecular biology  was worst and one of the metrics. But I don’t think the emphasis should be placed on that, I think the emphasis should be placed on all fields were getting worse.

Chris - How do you account for this?

William - With the data we had we tried to explore two possible reasons: one of them was: did the number of authors impact the readability because the number of authors has been growing over time. You often see four or five authors on a paper today, where in 1960 it was one or two. The number of authors does have an impact on the readability so if there’s more authors it’s generally less readable but that doesn’t explain the trend.

An additional hypothesis we had was that scientists may be drawing from an increasingly common vocabulary. We tried to see what were the 3,000 most common words that scientists use, then we split this list of 3,000 words up into several categories to isolate a category we called “general scientific jargon.” And these words were on the increase, scientists were drawing from this vocabulary of general scientific jargon.

Chris - Do you think it really matters though that some papers are a bit impenetrable because some people could argue well, I’m a molecular biologist and I don’t really care that much if an astrophysicist can’t read my molecular biology paper?

William - I’m very sympathetic to that view but, at the same time, this entire endeavour started when PhD students within the field of neuroscience were having a hard time reading some neuroscience, so it can hamper people within the subject itself. Then, in a much wider context, science is not just for scientists. People should be able to use scientific knowledge to make society better. If the wider parts of society cannot access papers such as scientific journalists or policy makers, if they’re having a hard time interpreting or understanding scientific text, that’s going to mean that science can’t be used as effectively in a wider context.

In 1967, a student at Cambridge University came across a series of strange pulsing signals that subsequently went on to transform the world of astronomy. What Jocelyn Bell Burnell had discovered were “pulsars” - small, dense rapidly spinning stars that fire off a lighthouse-like beam of radio waves as they go round. Dame Jocelyn Bell Burnell, as she is now, returned to her old college, that’s Murray Edwards in Cambridge recently to mark 50 years since her discovery by delivering a celebratory lecture. Izzie Clarke went along to listen...

Jocelyn - At that point in time, Cambridge University had one computer. It occupied a room of about this size and it had less memory than your laptop, and that was for the whole university. Our data came out on paper chart, rolls and rolls and rolls of it, because we didn’t have access to the computer. Perhaps just as well… because if we had had access to a computer with limited memory, we would not have programmed it to look for anything unexpected, like pulsars.

Izzie - Have you had many interviews in a room named after yourself?

Jocelyn - No I’ve never, I think, even been in a room named after myself.

Izzie - We’re here celebrating 50 years of your discovery of pulsars, and that was when you were here as a graduate student at the University of Cambridge. What were you initially working on?

Jocelyn - This was in the field of radio astronomy, which was a fairly new young field at that stage and what I was meant to be working on and, in fact, what my thesis was actually on was finding more quasars. Quasi stellar radio sources which are extremely distant and quite puzzling radio emitting objects.

Izzie - It was whilst studying these radio emitting quasars that Jocelyn came across a rather peculiar signal…

Jocelyn - The first thing that came to my attention was that there was a bit of signal that didn’t make sense. I’d got to the stage of recognising the quasars that I was meant to be seeing. I could see - I nicknamed it ‘a bit of scruff’ - there was quarter inch of this funny signal that I couldn’t make sense of in 500 yards, 600 yards, something like that. So it wasn’t very common, it wasn’t very extensive but, because I was being extremely thorough and keen to understand exactly what this new telescope was delivering, I was trying to check out what this was. It finally turned out that this little bit of scruff was a string of pulses, a string of blips about one and a third seconds apart.

...This is what came in on the recorder: blip, blip, missing. Blip, blip, blip, blip blip…

Well, first of all, nothing like that had been seen before, and nobody imagined that anything like that could exist. So it was really really surprising, we had to take quite a bit of time to convince ourselves that it really was a signal from outer space - from stars, and not some weird kind of interference that we hadn’t dreamt of.

For example, I remember wondering if it could be radar signals bouncing off the moon and into our radio telescope. Or could there be a satellite in a funny orbit which mimicked the motion of the stars? It took us several weeks of really hard work; then I found a second one, and a few weeks after that  I found a third and a fourth. So that really does begin to feel like a new kind of star, and then the question is: what on earth… well not on earth… what in the universe could give that kind of signal? What kind of star is this? It’s crazy!

Izzie - This baffling finding was the first detection of a pulsar, also known as a neutron star due to its neutron rich core. But how does a star give off this pulsing signal? Imagine a lighthouse with its two bright rotating beams that can be seen for miles away. Well, pulsars aren’t too dissimilar. This astronomical object spins round with two beams of radiation shooting out from each pole…

Jocelyn - We still don’t fully understand how radio beams are formed but the magnetic field, we’re pretty certain, has something to do with it. And, as this thing spins, if the beam sweeps across the Earth you see a pulse…

It turns out that these objects are small. They’re only about 10 miles across but they also are very very dense, very compact so they’ve got a lot of mass in them. They’ve got a thousand million, million, million, million tons of stuff in a ball 10 miles across. If you take a thimble and squeeze the 7 billion people on Earth into that thimble, then it weighs the same as if it were filled with stuff from one of these stars.

We now believe that it’s the end product, a life after death if you like, of a very big star which has done a catastrophic explosion which has basically killed off the star, dispersed 95% of the stuff out into space. But the 5% in the centre, the core, has been squashed in the explosion and become one of these stars.

Izzie - A nobel prize was awarded but it went to your supervisor. How did you feel at the time?

Jocelyn - I think at the time people expected me to be very angry, but I wasn’t. One of my colleagues, his wife heard the news, phoned him up at work and he came steaming through to my office to tell me and I think he expected to see me explode. I didn’t, because I’m also a political animal. There is no nobel prize in astronomy; there’s not one in mathematics either. Something to do with Professor Nobel and women and other professors, so certain areas he wasn’t going to leave his money to.

This was the first time the physics prize committee had deemed astronomy to have enough physics in it to award the physics prize so it was a huge, huge precedent. I was quite proud it was my stars that had convinced them. I knew that it was going to open the door for other astronomers and a couple of other astronomers have walked through that door subsequently. So yeah, it was very important.

As use of social media rises, people are asking questions about the link between heavy use and wellbeing. And, in particular, what about younger people amongst whom it’s extremely popular? Georgia Mills heard about what we know from Philip Powell at the University of Sheffield.

Philip - The evidence on this is mixed. The first thing to say is that social media can have positive effects on well-being by decreasing loneliness, providing sources of support for people and even providing a venue to affirm their sense of self-worth by reviewing their profile.

But what we have as well as that is a series of large representative national survey studies that have been carried out across different countries that show a significant negative relationship between the time spent on social networking and people's well-being. We know that these effects are largely concentrated at the top end of use so that people who spend an excessive time on social media, which is normally defined as around greater than two hours per day. Some recent research by scholars at Oxford University has actually shown that at low to moderate amount of social media use can be beneficial and they’ve termed this the “Goldilocks effect.”

Georgia - Okay. Some use is good but a lot of use is associated with negative things, but how do we know that who are sort of less well aren’t just more likely to spend hours and hours on social media because of this?

Philip - It’s definitely a concern and the majority of research is associational that just shows a correlational relationship between social media use and lower well-being. There have been some studies that have looked at how the two things may interact over time, so it’s been shown that changes in social media use are associated with changes in well-being. But that still doesn’t mean that the change in, for example, Facebook usage causes the change in well-being, it’s possible that another variable may influence the two things independently.

In our own research we’ve tried to overcome this by using sophisticated statistical techniques. They are used when we don’t have experimental data but we are able to use additional data that has a one way affect on our outcomes. We can, essentially, estimate the association between social media use and this additional data, which was internet connection speeds from Ofcom. And by estimating the association between those two things and the strength of the association with well-being we’re able to derive as close to causal relationships as possible.

Georgia - And this is still indicating that a lot of use is negative. So what kind of effects is it having on well-being and do we have any ideas why?

Philip - These things include reduced life satisfaction, increased anxiety and depression, and reduced happiness. These are things that can be distinguished but are generally related to one another. The method in which increased social media use may result in lower well-being is likely to be multifactorial. It may involve, for example, instances of cyber bullying, negative comparisons with others, exposure to inappropriate content online. And also through its association with disruption to physical and healthy daily activities such as sleep and exercise and other positive activities for our well-being.

Georgia - You mentioned cyber bullying there. Facebook previously only allowed over 13 year olds to use their site, but recently they’ve launched Messenger Kids, which is a service aimed as just pre-teens. So do we know how social media affects young people in particular?

Philip - The first thing to point out is often children under the age of consent are frequently using social networking sites already. In our own data we found worse effects of social media use on well-being on those that were aged 13 and over, and not at those that were younger and there are a number of reasons of why this may be the case. We also know from separate data that cyber bullying increases over time in the early teen years. We also know that there are increased pressures on children and young people to fit in in the teen years.

Georgia - Social media is obviously a very broad term. There’s lots of different types of social media and there’s lots of different ways to use it, so do we know what kind of different effects different social media has?

Philip - There was a recent survey by the Royal Society for Public Health for 14-24 year olds and they had there participants rank the main social media platform, so that’s Facebook, Instagram, Snapchat, Twitter and YouTube. They had them rank them on a range of health related factors including depression, body image, experience of bullying.

What they found is that YouTube came out as the most positive and Instagram was the most negative, and they don’t actually elaborate on why that may be the case. But we could, for example, hypothesise that because Instagram is a platform that involves user-generated photos, and we know that idealised and filtered photos are particularly problematic for young people’s well-being.

The other thing to mention is it’s been a distinction throughout the literature between passive and active use. Passive use describes things like looking at people’s profile pages and liking, whereas active use involves actively connecting and chatting with people, and it tends to be the passive use that is particularly problematic for well-being.

Georgia - Do we know anything about how social media affects our ability to learn; I suppose specifically with children?

Philip - No. I think there’s a positive research in this area, and this is something that we’d like to look into in the future.

Georgia - It’ll be interesting to see what that says; it certainly makes procrastinating easier. What do we do about this; do we need to do anything?

Philip - There are three main approaches we could take and they’re not all mutually exclusive. The first is that we try to reduce or restrict the amount of time that children and young people, and maybe even adults, spend on social media. The Royal Society for Public Health has called, for example, pop up warnings on heavy usage on social media sites and this is supported by a majority of young people that they surveyed.

A second approach is that we focus on this idea of usage. It’s not the amount of time per se but it’s what people are doing online. We need to generate platforms for social media that encourage active use and discourage passive browsing of information and social comparison.

Finally, there’s the idea that’s supported by places like the Education Policy Institute that we actually have a duty to educate our young people in the safe use of social media and equip them with digital skills so they can cope with problematic behaviours online.

Social media might have some interesting applications for monitering mental health. University of Vermont statistician Chris Danforth is developing computer algorithms that he says can spot people with depression just by looking at the content and compositions of photographs they’re posting onto the social media platform Instagram. In tests he’s achieving up to a 70% pick-up rate. Georgia Mills spoke to Chris about his work.

Chris - There have been a number of studies in the last few years looking at aspects of our behaviour that we reveal through social media. In particular, studies that we’ve been involved in have been looking at trying to assess someone’s mental health from aspects of images they post to Instagram and messages they write on Twitter.

Georgia - How have you looked into this?

Chris - What we did was recruit individuals who had been diagnosed with depression by a psychiatrist and were active on social media at the time. We asked them for access to their social media feeds, so we compared picture’s they took with pictures taken by a control group who had not been diagnosed with depression.

What we found was that individuals who had been diagnosed with depression, their pictures tend to be bluer, and darker, and greyer. They tended to have less faces in them and these results are consistent with what psychiatrists know about how depression affects people. It literally causes them to see the world with less colour in it, and they spend less time in large groups of people and social interactions.

While those findings weren’t particularly surprising, what’s really exciting about that particular study from our perspective is that when we restricted our computer model to only have access to pictures posted by people prior to the date that they were formally diagnosed, it still picked up on these differences. That’s an indication that we could be able to get individuals who are suffering from depression in front of a doctor sooner.

Georgia - Oh wow! So you could quantify these pointers like having blacker and bluer pictures, and these things appeared before people had actually got a clinical diagnosis?

Chris - That’s right. And the results, they’re consistent with what people are finding looking at other sources of social media as well. We looked in a separate study at depression and PTSD, and identified predictors of those health states from words that people were using on Twitter and their behaviour: frequency of their posts, how likely they were to include links in their posts. And there were indicators, as well, that there were differences prior to the date that they were formally diagnosed.

So I think that the results of our study are promising, but they’re really just a proof of concept. There’s a small group of a few hundred people in each of these studies and it’s not clear that this would translate to the average person using Instagram or Twitter. But the goal is to try and figure out how to leverage all of the information that we give our mobile phone about us: our tone of voice, the words we use, the people we communicate with. This sort of data it’s incredibly private so if we can protect it but yet, at the same time, give algorithms access to information that’s predictive about our health state, we could be connecting with our doctor sooner. For example, the doctors could have access to a lot more information than they would get from a typical yearly checkup interview.

Georgia - Do you see this being used by the social media companies themselves?

Chris - Certainly companies know a lot about you, even if you’re not using it, just from what your friends are doing on the site. I do expect that there are going to be situations where social media companies are selling advertising spots for people who are suffering from mental health problems potentially without even intending to, or realising that they’re doing so. That’s something that I think is really important right now is that we start having a conversation with each other about how to protect this sort of data.

This particular study was done by a few people with limited resources but certainly, if we could do it, then a company like Instagram or Facebook or Twitter, they could use this data to try and make money. We’d like for them to use it to try and help us be happier and healthier.

Georgia - I suppose that is a worry, people will be worried about their privacy; that people could see that they’re depressed before maybe they know themselves?

Chris - I think that we reveal a lot more about ourselves online with our digital footprint than we’re aware of.  Part of doing research studies like this in communicating the results of these studies to people is to help educate the population about what it is that they need to be aware of when they’re on the internet.

Georgia - Is there a way the social media companies could use this information for good?

Chris - Certainly Facebook and Instagram are active in trying to provide mental health resources to people who, for example, search for the word depression or use words that have been seen to be predictive of self-harm. They have teams working on trying to get individuals who are suffering from the problems access to people sooner. And that is a combination of artificial intelligence and actual people who are then called in to virtually try and address whatever’s going on and maybe, potentially, dispatch police officers to attempt to rescue someone. So companies are working on that sort of thing.

Stepping back to the picture of public health, there are a number of other studies, some of which we’ve done, showing that things that you might like to quantify about how well a city or a society are functioning, those things can be inferred from the words that are used if you look at particular geographic areas. We’ve shown, for example, that population scale, health rankings, like the percentage of people who are obese, or who suffer from diabetes, those things can be inferred from just the words that people use on Twitter.

Well-being surveys that are done by Gallup can be inferred without asking any questions simply by seeing how often people use happy and sad words in different states, for example, in the US. So there are going to be applications for this sort of public health instrument building that people are going to develop.