Tag: facebook

Dislike of the like button

When you read histories or profiles of Facebook (the “original” product), there are two inflexion points that are likely to get mentioned. One is the news feed, where updates from all your friends are shown in “random” order on your wall (along with a bunch of ads). The other is the “like” button.

The like button was transformative in that it allowed people to express their acknowledgement of a post without really having to write a word. It was the lazy person’s best friend. One bit to show that they have “put attendance” or “shown support” or just acknowledged that they had been there.

More importantly, from Facebook’s perspective, this gave them tremendous data (at low cost to the users) in terms of what people wanted to see more or less of on their newsfeeds. Their algorithms quickly started working on this, and people’s feeds got tuned. Engagement went up. Ad sales went up. Everything was good.

And then the like button started appearing everywhere. I remember Twitter changing one button – from something else to “like”. LinkedIn introduced it, too. Soon, there were several versions of the like button representing different kinds of emotions. I don’t even understand what most of these buttons mean.

It was only a matter of time that this button would make its way to WhatsApp. It’s been there for a few years now but I haven’t really taken to using it. And now I’m thinking it’s actually a problem.

The problem with the like button (or any other such emojis) on WhatsApp is that it is a conversation stopper. Literally. It is basically a message that cannot be replied to, or acknowledged (you can’t like a like). So once one of the parties puts the emoji, there is nothing more to be done, but to move on.

Long ago, conversations would go like this:

“Hey man, happy birthday”.
“Thanks a lot. how are you doing? how’s the job / wife / kid? ”
Conversation continues….

Or

“Hey, check out this link”
Either no response, or “Thanks, I’ll check it out”, or (best case) “Very very interesting. This is my take on this. And see this other article”

Now all this is history. You say Happy Birthday, and people react right there with some emoji. You send them a link. They react with a thumbs up sign on the same message. There is nothing else to do. There is no conversation.

I’ve started regarding the like emoji on WhatsApp as rude (the only exception is the laughing emoji, to react to jokes, and that is ONLY to be used in groups). If someone reacts with an emoji (especially the thumbs up, or folded hands), I take that as “ok fine, I don’t want to talk to you” sign.

Maybe I’m becoming old.

 

Social Media Regulation

To use (and abuse) my good friend Sangeet Paul Choudary‘s framework, Twitter is both a pipe and a platform. Whether it is a pipe or a platform depends on how you use it.

I always use Twitter in the “latest tweets” mode, which means that tweets from people I follow are shown to me in the order in which they happen, with most recent tweets on top. Twitter has no role in showing what tweets I see or not see. Someone I follow says something, it will come in its appointed place. This is the twitter in its “pipe avatar”. It is no different from reading blogs through an RSS feed. Twitter is just a pipe to convey these tweets to me.

However, this “latest tweets” is not the default mode for Twitter. The default mode is what I think it calls “top tweets” or something. This is the algorithmic timeline that Twitter launched a few years back. Here, twitter’s algorithms determine what you should see. Whether a tweet gets shown to you at all, whether you follow someone whose tweets you are shown and what order tweets are shown to you in – none of these are under your control. It is twitter’s (rather, and understandably, opaque) algorithm that determines this. This is twitter operating in its “platform avatar”, since it, through its algorithms, is effectively controlling the content you see.

Why is it important if twitter is a pipe or a platform? It has to do with regulation. I understand that twitter and facebook have recently suspended Donald Trump’s account. Some people are saying this is unfair, and that it is a step too far for social media. Others are using this as an excuse for more social media regulation.

My contention is that whether social media should be regulated or not is guided by whether social media is a pipe or a platform.

If social media is a pipe, like twitter in its latest tweets (or “traditional”) format, then regulation is unnecessary. In this situation, people are served tweets only because they’ve chosen to receive them. If some account only tells lies, so be it. People follow parody accounts all the time. By censoring accounts, twitter is denying people the right to see the thing they have subscribed to see. Any regulation or censorship means that people are not getting what they have signed up for.

On the other hand, in the algorithmic timeline format, one can make a case for some kind of regulation or censorship. This is because the platform here, either implicitly or explicitly, chooses what the user sees. And if the platform’s algorithms mean that lies and hatred and outrage get amplified, then that is a problem. If a tweet from a parody account suddenly appears in my timeline, it can throw me off and drive me bonkers. And that is not “fair”.

Then again, while one can make a case for censorship in the “platform model”, I’m not advocating that regulation or censorship is necessary. Yes, the opaque algorithms can amplify bad shit, but how are you going to even regulate that?

You want algorithms to be passed by some central board? You want the platform to deplatform your opponents but not your folks? You want a profit-maximising (likely monopoly) private entity to determine what is “truth” and what is not? Irrespective of how the regulation or censorship is defined, it is rather easy for it to have consequences that the designers of the regulation or censorship have least expected.

In any case, these occasional cals for censorship or regulation or cancellation are the reasons why I put most of my better arguments on this blog, which gets delivered through this pipe called RSS feeds.

Advertising

When I first joined Instagram in 2013 or 2014, the first thing that fascinated me about the platform was the quality of advertisements. At that point in time, all advertisements there looked really good, like the pictures that the platform was famous for helping sharing.

It wasn’t like the clunky ads I would see elsewhere on the internet, or even on Facebook – which mostly stuck out like a sore thumb in the middle of whatever content I was consuming at that point in time. Instagram advertisements looked so good that I actually paid them considerable attention (though I hardly clicked on them back then).

Over the years, as Facebook has gotten to know me better (I hardly use Facebook itself nowadays. But I use a lot of Instagram. For now I’ll believe Facebook’s claim that my WhatsApp information is all encrypted and Facebook doesn’t learn much about me through that), and the advertisements have gotten better and more relevant.

Over the last one year or so (mostly after I returned to India) I’ve even started clicking on some of the ads (yes they’ve become that relevant), giving Facebook even more information about myself, and setting off a positive feedback loop that makes the advertisements more relevant to me.

Over the years I’ve attended talks by privacy experts about the privacy challenges of this or that platform. “They’ll get all this information about you”, they say, “and then they can use that to send you targeted advertisements. How bad is that?”. If I think about all the problems with telling too much about myself to anonymous platforms or companies, receiving better targeted advertisements is the least of my worries.

As a consumer, better targeted ads means better information to me. Go back to the fundamentals of advertising – which is to communicate to the customer about the merits of a particular product. We think advertising can be annoying, but advertising is annoying only when the advertisements are not relevant to the target customer. 

When advertisements are well targeted, the customer gets valuable information about products that enables them to make better decisions, and spend their money in a better fashion. The more the information that the advertiser has about the end customer, the better the quality (defined in terms of relevance) the advertisements that can be shown.

This is the “flywheel” (can’t imagine I would actually use this word in a non-ironic sense) that Facebook and affiliated companies operate on – every interaction with Facebook or Instagram gives the company more information about you, and this information can be used to show you better targeted advertisements, which have a higher probability of clicking. Because you are more likely to click on the advertisements, the advertiser can be charged more for showing you the advertisement.

Some advertisers have told me that they elect to not use “too much information” about the customer while targeting their advertisements on Facebook, because this results in a much higher cost per click. However, if they look at it in terms of “cost per relevant click” or “cost per relevant impression”, I’m not sure they would think about it the same way.

Any advertisement shown to someone who is not part of the intended target audience represents wastage. This is true of all forms of advertising – TV, outdoor, print, digital, everything. It is no surprise that Facebook, by helping an advertiser advertise with better (along several axes) information about the customer, and Google, by showing advertisements after a customer’s intent has been established, have pretty much monopolised the online advertising industry in the last few years.

Finally, I was thinking about advertising in the time of adblockers. Thanks to extensive use of ad-blockers (Safari is my primary browser across devices, so ad blocking is effective), most of the digital advertisements I actually see is what I see on Instagram.

Today, some publication tried to block me from reading their article because I had my ad-blocker on. They made a sort of moral pitch that advertising is what supports them, and it’s not fair if I use an ad-blocker.

I think they should turn to banner ads. Yes. You read that right.

To the best of my knowledge, ad blockers work by filtering out links that come from the most popular ad exchanges. Banner ads, which are static and don’t go through any exchange, are impossible to block by ad-blockers. The problem, however, is that they are less targeted and so can have higher wastage.

But that is precisely how advertising in the offline versions of these newspapers works!

Something is better than nothing.

Social Media Addiction

Two months back I completely went off social media. I deleted the instagram app from my phone and logged out of Instagram, Twitter, LinkedIn and Facebook on my computer. I needed a detox. And I found myself far more focussed and happier after I did that. And I started writing more here.

My first month off social media was strict. No social media under any circumstance. This was necessary to get rid of the addiction. Then, since I came back from the Maldives trip, I’ve been logging into various social media accounts on and off (about once a day on average) just to see if there are any messages and to browse a bit.

I only do it from my computer, and at a time when I’m not fully working. And as soon as the session is over I make sure I log out immediately. So the instinctive adrenaline-seeking opening of social media tabs is met by a login screen, which is friction, and I close the tab. So far so good.

In my infrequent returns to social media I’ve found that the most “harmless” are LinkedIn and Facebook (it might help that I don’t follow anyone on the latter, and if I want to check out what’s happening in someone’s life I need to explicitly go to their profile rather than them appearing on my timeline). LinkedIn is inane. Two or three posts will tell you it’s a waste of time, and I quickly log out. Facebook is again nothing spectacular.

Twitter is occasionally interesting, and I end up scrolling for a fair bit. For the most part I’m looking for interesting articles rather than look at twitter arguments and fights. I’m convinced  that twitter statements and arguments don’t add much value – they’re most likely ill thought out. Instead a link to a longer form piece leads me to better fleshed out arguments, whether I like it or not.

Mostly after a little bit of twitter scrolling, I find enough pieces of outrage, or news/political stuff that I get tired and log out. It’s only when I really need an adrenaline rush and don’t mind people cribbing that I stay on twitter for a bit of a long time (over five minutes).

Instagram, on the other hand, is like smoking cigarettes. When I smoked my first cigarette in 2004 I felt weak in the knees and a sort of high. It was in my final year of college, so I’d had enough friends tell me that cigarette smoking is addictive. And my first cigarette told my why exactly it was addictive.

So I made a policy decision at that moment that I’d limit myself to a total of one cigarette a year. I’ve probably averaged half a cigarette a year since then. My last one was in 2016.

Instagram is really addictive. It’s full of pictures, and if you avoid the really whiny accounts there is little negativity or politics. People make an effort to look nice, and take nice pictures, for instagram. So there is a lot of beauty in there. And if I choose to, especially when I’m logging in after a long time, I can keep at it for hours.

Instead I need to be conscious that it’s addictive (like my one cigarette a year rule), and pull myself away and force myself to log out. This also means that while I open twitter about once a day, Instagram is less than once a week.

I wonder what this means about the sustainability of social networks!

Context switches and mental energy

Back in college, whenever I felt that my life needed to be “resurrected”, I used to start by cleaning up my room. Nowadays, like most other things in the world, this has moved to the virtual world as well. Since I can rely on the wife (:P) to keep my room “Pinky clean” all the time, resurrection of life nowadays begins with going off social media.

My latest resurrection started on Monday afternoon, when I logged off twitter and facebook and linkedin from all devices, and deleted the instagram app off my phone. My mind continues to wander, but one policy decision I’ve made is to both consume and contribute content only in the medium or long form.

Regular readers of this blog might notice that there’s consequently been a massive uptick of activity here – not spitting out little thoughts from time to time on twitter means that I consolidate them into more meaningful chunks and putting them here. What is interesting is that consumption of larger chunks of thought has also resulted in greater mindspace.

It’s simple – when you consume content in small chunks – tweets or instagram photos, for example, you need to switch contexts very often. One thought begins and ends with one tweet, and the next tweet is something completely different, necessitating a complete mental context switch. And, in hindsight, I think that is “expensive”.

While the constant stream of diverse thoughts is especially stimulating (and that is useful for someone like me who’s been diagnosed with ADHD), it comes with a huge mental cost of context switch. And that means less energy to do other things. It’s that simple, and I can’t believe I hadn’t thought of it so long!

I still continue to have my distractions (my ADHD mind won’t allow me to live without some). But they all happen to be longish content. There are a few blog posts (written by others) open in my browser window. My RSS feed reader is open on my browser for the first time since possibly my last twitter break. When in need of distraction, I read chunks of one of the articles that’s open (I read one article fully until I’ve finished it before moving on to the next). And then go back to my work.

While this provides me the necessary distraction, it also provides the distraction in one big chunk which doesn’t take away as much mental energy as reading twitter for the same amount of time would.

I’m thinking (though it may not be easy to implement) that once I finish this social media break, I’ll install apps on the iPad rather than having them on my phone or computer. Let’s see.

A one in billion trillion event

It seems like capital markets quants have given up on the lognormal model for good, for nobody described Facebook’s stock price drop last Thursday as a “one in a billion trillion event”. For that is the approximate probability of it happening, if we were to assume a lognormal model of the market.

Created using Quantmod package. Data from Yahoo.

Without loss of generality, we will use 90 days trailing data to calculate the mean and volatility of stock returns. As of last Thursday (the day of the fall), the daily mean returns for FB was 0.204%, or an annualised return of 51.5% (as you can see, very impressive!). The daily volatility in the stock (using a 90-day lookback period again) was 1.98%, or an annualised volatility of 31.4% . While it is a tad on the higher side, it is okay considering the annual return of 51.5%.

Now, traditional quantitative finance models have all used a lognormal distribution to represent stock prices, which implies that the distribution of stock price returns is normal. Under such an assumption, the likelihood of a 18.9% drop in the value of Facebook (which is what we saw on Thursday) is very small indeed.

In fact, to be precise, when the stock is returning 0.204% per day with a vol of 1.98% per day, the an 18.9% drop is a 9.7 sigma event. In other words, if the distribution of returns were to be normal, Thursday’s drop is 9 sigmas away from normal. Remember that most quality control systems (admittedly in industrial settings, where faults are indeed governed by a nearly normal distribution) are set for a six sigma limit.

Another way to look at Thursday’s 9.7 sigma event is that again under the normal distribution, the likelihood of seeing this kind of a fall in a day is $math ~10^{-21}$. Or one in a billion trillion. In terms of the number of trading days required for such a fall to arrive at random, it is of the order of a billion billion years, which is an order of magnitude higher than the age of the universe!

In fact, when the 1987 stock market crash (black monday) happened, this was the defence the quants gave for losing their banks’ money – that it was an incredibly improbable event. Now, my reading of the papers nowadays is sketchy, and I mostly consume news via twitter, but I haven’t heard a single such defence from quants who lost money in the Facebook crash. In fact, I haven’t come across too many stories of people who lost money in the crash.

Maybe it’s the power of diversification, and maybe indexing, because of which Facebook is now only a small portion of people’s portfolios. A 20% drop in a stock that is even 10% of your portfolio erodes your wealth by 2%, which is tolerable. What possibly caused traders to jump out of windows on Black Monday was that it was a secular drop in the US market then.

Or maybe it’s that the lessons learnt from Black Monday have been internalised, and included in models 30 years hence (remember that concepts such as volatility smiles and skews, and stochastic volatility, were introduced in the wake of the 1987 crash).

That a 20% drop in one of the five biggest stocks in the United States didn’t make for “human stories” or stories about “one in a billion billion event” is itself a story! Or maybe my reading of the papers is heavily biased!

PostScript

Even after the spectacular drop, the Facebook stock at the time of this update is trading at 168.25, a level last seen exactly 3 months ago – on 26th April, following the last quarter results of Facebook. That barely 3 months’ worth of earnings have been wiped out by such a massive crash suggests that the only people to have lost from the crash are traders who wrote out of the money puts.

Algorithmic curation

When I got my first smartphone (a Samsung Galaxy Note 2) in 2013, one of the first apps I installed on it was Flipboard. I’d seen the app while checking out some phones at either the Apple or Samsung retail outlets close to my home, and it seemed like a rather interesting idea.

For a long time, Flipboard was my go-to app to check the day’s news, as it conveniently categorised news into “tech”, “business” and “sport” and learnt about my preferences and fed me stuff I wanted. And then after some update, it suddenly stopped working – somehow it started serving too much stuff I didn’t want to read about, and when I tuned (by “following” and “unfollowing” topics) my feed, it progressively got worse.

I stopped using it some 2 years back, but out of curiosity started using it again recently. While it did throw up some nice articles, there is too much unwanted stuff in the app. More precisely, there’s a lot of “clickbaity” stuff (“10 things about Narendra Modi you would never want to know” and the like) in my feed, meaning I have to wade through a lot of such articles to find the occasional good ones.

(Aside: I dedicate about half a chapter to this phenomenon in my book. The technical term is “congestion”. I talk about it in the context of markets in relationships and real estate)

Flipboard is not the only one. I use this app called Pocket to bookmark long articles and read later. A couple of years back, Pocket started giving “recommendations” based on what I’d read and liked. Initially it was good, and mostly curated from what my “friends” on Pocket recommended. Now, increasingly I’m getting clickbaity stuff again.

I stopped using Facebook a long time before they recently redesigned their newsfeed (to give more weight to friends’ stuff than third party news), but I suspect that one of the reasons they made the change was the same – the feed was getting overwhelmed with clickbaity stuff, which people liked but didn’t really read.

Basically, there seems to be a widespread problem in a lot of automatically curated news feeds. To put it another way, the clickbaity websites seem to have done too well in terms of gaming whatever algorithms the likes of Facebook, Flipboard and Pocket use to build their automated recommendations.

And more worryingly, with all these curators starting to do badly around the same time (ok this is my empirical observation. Given few data points I might be wrong), it suggests that all automated curation algorithms use a very similar algorithm! And that can’t be a good thing.

Commenting on social media

While I’m more off than on in terms of my consumption of social media nowadays, I find myself commenting less and less nowadays.

I’ve stopped commenting on blogs because I primarily consume them using an RSS reader (Feedly) on my iPad, and need to click through and use my iPad keyboard to leave comments, a hard exercise. And comments on this blog make me believe that it’s okay to not comment on blogs any more.

On Facebook, I leave the odd comment but find that most comments add zero value. “Oh, looking so nice” and “nice couple” and things like that which might flatter some people, but which make absolutely no sense once you start seeing through the flattery.

So the problem on Facebook is “congestion”, where a large number of non-value-adding comments may crowd out the odd comment that actually adds value, so you as a value-adding-commentor decide to not comment at all.

The problem on LinkedIn is that people use it mostly as a medium to show off (that might be true of all social media, but LinkedIn is even more so), and when you leave a comment there, you’re likely to attract a large number of show-offers who you are least interested in talking to. Again, there’s the Facebook problem here in terms of congestion. There is also the problem that if you leave a comment on LinkedIn, people might think you’re showing off.

Twitter, in that sense, is good in that you can comment and selectively engage with people who reply to your comment (on Facebook, when all replies are in one place, such selective engagement is hard, and you can offend people by ignoring them). You can occasionally attract trolls, but with a judicious combination of ignoring, muting and blocking, those can be handled.

However, in my effort to avoid outrage (I like to consume news but don’t care about random people’s comments on it), I’ve significantly pruned my following list. Very few “friends”. A few “twitter celebrities”. Topic-specific studs. The problem there is that you can leave comments, but when you see that nobody is replying to them, you lose interest!

So it’s Jai all over the place.

No comments.

Twitter and negativity

One of the reasons that sparked my departure from social media platforms such as Facebook and Twitter two weeks back was an argument with my wife where she claimed that Twitter had made me too negative, and highly prone to trolling (even in “real life”). Accepting a challenge from her, I offered to go through my tweets over the last few months, and identify those that were negative. I also offered to perform a similar exercise with my blog.

I started off with the intention to go through tweets in the last one year and delete anything that was negative or “troll-y”. I allocated myself an hour to accomplish this, along with a similar exercise for my blog.

I must have spent fifty minutes going through my twitter feed, and didn’t manage to go back more than two months. I was surprised by my own sheer volume of tweeting. What was more surprising was the amazing lack of insight in most of those tweets – there were horrible PJs that I’d cracked just because I could, there were random replies to other people which didn’t add any kind of value, there was outrage about the lack of outrage and some plain banal life stuff (apart from some downright trolly stuff which I deleted).

It made for extremely painful reading, and I could hardly recognise myself from my own tweets. Apart from some personal markers, I would find it hard to recognise most of these tweets as my own if they were to be presented to me a few months later. It was a clear indication that it was time to exit twitter (though since I have a rather kickass username there I’m not deleting my account).

The ten minutes I spent that day going through this blog, however, was a sheer delight. I did end up deleting a couple of outragey posts (both of which were essentially collections of tweets which I’d collated for posterity), but most of my posts were mostly sheer delight! There was some kind of insight in each of my posts, and I’d lie if I were to say that I’m not proud of what I’ve written.

It’s not that I’ve not written shit on this blog (or its predecessor), having written posts as late as 2008 which I’m definitely not proud of. What I’ve noticed, however, is that I’ve evolved over time, and my writing style has been refined, and I think I continue to add significant value to my readers.

Twitter’s constant engagement feature, however, meant that it was hard to evolve there and hard to escape from the cycle of banal and negative tweets. My tweets from this February are unlikely to be qualitatively very different from those 5 years back, and that’s not a positive thing to say.

The thing with Twitter is that its short format encourages a “shoot first ask questions later” kind of thinking. You end up posting shit without thinking through it, and without having to construct a reasonable argument. This encourages outrage, and posting banal stuff. Spending one minute typing out a banal tweet is far lower cost than spending 20 minutes typing out a banal blog post – the latter is unlikely to be written unless there’s some kind of insight in it.

Outrage is one thing, but what’s really got to me with respect to twitter is its sheer ordinariness, and temporality (most tweets lose value a short period of time after they’re posted). It’s insane that it’s taken me so long (and three longish sabbaticals from twitter) to find out!

The problem with Twitter

Starting from the mid-2000s, the dominant method to consume content was to follow individual blogs through RSS Feed readers such as Bloglines or Google Reader. You followed specific blogs, most of which (unlike this one) had content on specific topics.

So when I wanted to learn up on economics, I started following Marginal Revolution and Econlog. When I wanted to follow the global financial crisis, I added Felix Salmon and a couple of other blogs (which I don’t remember now). All I needed to do to read on specific topics was to follow specific people.

And then Google Reader Shared Items happened. Now, you didn’t really need to follow specific blogs, for there was a social network where people would share interesting stuff that they read. Now you could outsource following blogs to friends who became curators. So there was this one friend who would share pretty much every interesting post on Mashable. Another shared every interesting post from this blog called The Frontal Cortex. I didn’t need to follow these blogs. My “curator friends” shared the best pieces with me (and I know people relied on me for Econlog etc.).

Then around the turn of the decade, Twitter replaced Google Reader Shared Items as the primary content discovery platform. A couple of years later, Google would decommission Reader. The thing with Twitter was that the movement from following specific ideas and sites to following “curators” was complete.

While twitter also functions as a “normal” social network, a major function is the sharing of ideas, and so everyone on twitter is essentially a curator, sharing with her followers what she wants them to read. There is also scope for adding comments here, and adding one’s opinion to the content. This adds a sort of richness to the content, and people can filter stuff accordingly, without consuming everything one’s friend has shared.

The downside, however, is that you are forced to consume the opinions and links shared by everyone you follow. There might be someone who I might be following for his curation of technology links, but it might happen that he might also tweet heavily on politics, which I’m hardly interested in. There is an option to turn off retweets (which I’ve used liberally) but even so, there is a lot of “unwanted content” you have to consume from people. And since it is “opinion first” (and link later), you are forced to consume people’s opinion even if you’re just browsing their timeline.

What we need in Twitter is a way to curate people’s opinions on topics. For example, I might be interested in Person A’s opinion on politics but not anything else. Person B might offer good opinions on economics but might be lousy on other things. Person C might be good for technology and sports. And so forth.

Of course, you can’t charge people with classifying their own tweets – that will add too much friction to the process. What you need is an intelligent process or app that can help classify people’s tweets and show you only what you want to know.

I can think of a couple of designs for the app – one could be where you could tell it not to show any more tweets from someone on a particular topic (or block a topic itself). Another is for you to upvote and downvote tweets, so that the app learns your preferences and shows you what you want.

Yet, I’m not confident that such an app will be built. The problem is that twitter has been notorious in terms of cutting off access to its API to apps built on it, or cutting permissions of what apps can see (Facebook is as guilty here). So it’s a massive challenge to get people to actually invest in building twitter apps.

Twitter as it exists currently doesn’t work for me, though. I repeatedly find the problem that there is way too much outrage on my timeline, and despite mercilessly cutting the number of people I follow, I find that it’s a slippery slope and otherwise interesting people continue to tweet about stuff that I don’t want to read about. And so my engagement is dipping.

I don’t need twitter itself to do anything about it. All they should do is to send out credible signals that they’ll not pull the rug under the feet of developers, so that APIs can be developed, which can make the platform a much more pleasant experience for users.