Category Archives: Gadgets and Technology

Today’s social interactions: “data is our currency”

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Want to interact with the culturally literate crowds of today? You need to be aware of lots of online data:

Whenever anyone, anywhere, mentions anything, we must pretend to know about it. Data has become our currency. (And in the case of Bitcoin, a classic example of something that we all talk about but nobody actually seems to understand, I mean that literally.)…

We have outsourced our opinions to this loop of data that will allow us to hold steady at a dinner party, though while you and I are ostensibly talking about “The Grand Budapest Hotel,” what we are actually doing, since neither of us has seen it, is comparing social media feeds. Does anyone anywhere ever admit that he or she is completely lost in the conversation? No. We nod and say, “I’ve heard the name,” or “It sounds very familiar,” which usually means we are totally unfamiliar with the subject at hand.

Knowing about all of the latest Internet memes, videos, and headlines may just be the cultural capital of our times. On one hand, cultural capital is important. This is strikingly seen in the influence of Pierre Bourdieu in recent decades after Bourdieu argued different social classes have different cultural tastes and expressions. Want to move up in the world? You need to be able to operate in the cultural spheres of the upper classes. On the other hand, the writer of this article suggests this cultural capital may not be worth having. This Internet data based cultural capital emphasizes a broad and populist knowledge rather than a deep consideration of life’s important issues. If we are all at the whim of the latest Internet craze, we are all chasing ultimately unsatisfying data.

But, I think you can take this another direction than the long debate about what is proper cultural literacy. I recently heard an academic suggest we should ask one question about all of this: how much do we get wrapped up in these online crazes and controversies versus engaging in important relationships? Put in terms of this article, having all the data currency in the world doesn’t help if you have no one to really spend that currency with.

 

Update on the Internet versus other forms of media

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Derek Thompson provides an update on how people use the Internet in comparison to television and other media:

Eyes move faster than ads. It was true for TV: In 1941, when the first television ads appeared with local baseball games, radio and print dominated the media advertising market. Now it’s true for mobile, which is practically a glass appendage attached to working Americans and commands more attention than radio and print combined, even though it only commands 1/20th of US ad spending. Google and Facebook own the future of mobile advertising, for now. But the present of mobile monetization isn’t ads. It’s apps…The second chart that really struck me from the Meeker report shows the growth of the mobile biz since 2008, which has exploded from $2 billion to $38 billion. I never would have guessed that two-thirds of the mobile business comes from paid apps rather than advertising. It’s an interesting reversal from the desktop ecosystem, where just about every Internet property I use is free and supported with third-party advertising. When you combine this graph (basically: Mobile is an app industry, with a side of ads) and the previous graph (basically: The future of attention is mobile), you begin to see just how important it is for media companies to promote high-quality apps for their stuff…

If you’re wondering why Facebook spent a bajillion dollars on WhatsApp and Instagram (and offered more bajillions to Snapchat), just look at this graph for a split-second. The Internet as you know is essentially a series of tubes optimized for facilitating the distribution of photos. Although Facebook’s share of that photo market isn’t growing, WhatsApp and Snapchat have exploded. This feeds into a larger point that Meeker makes in the presentation, which is that the mobile Internet has been a boon for discrete, simple functions. WhatsApp is simple. Snapchat is simple. Timelines are simple. Simple actions and interfaces are thriving on mobile, more than services like Facebook which offer a more complex suite of functions…

– British people watch the most TV.
– The Chinese, Vietnamese, and Russians spend the most time on desktop computers.
– Nigeria is the most addicted to their smartphones.
– Nobody loves tablets more than the Philippines and Indonesia.

Some fascinating info. The quick rise of the mobile device is truly remarkable but it is worth noting that it hasn’t supplanted television and other media just yet. In fact, perhaps part of its appeal is that it is able to co-opt other forms of media: print, TV, and radio can all migrate to a single smartphone screen.

A video goes viral with 320,000+ views in one week?

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This silent newsreel of the 1919 Black Sox World Series is a great find. A news story about the video suggests it went viral with over 320,000 views in its first week online. Is this enough views to go viral?

This is an ongoing issue for stories and reports regarding online behavior. When does something go from being an online object of interest to some people to being a trend? Reporters often find Facebook groups or a few blog posts and turn that into a trend. Perhaps this is better than interviewing a few people on the street – also still done – but there are plenty of online groups, tweets, and posts.

We need some sort of metric or guidelines for making such proclamations. Unfortunately, there is little agreement about this for websites: should we count page views, unique visitors, click-throughs or something else? Should we just count the number of Twitter followers even though they can be purchased? Other mediums have agreed-upon metrics like Nielsen ratings or book sales or digital downloads.

In the meantime, I would suggest 342,000 viewers is not quite going viral.

Almost 25% of Spotify songs skipped in first five seconds – and other song-skipping data

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Here is some fascinating data about song-skipping patterns from Spotify users:

  • Nearly a quarter of all songs on Spotify get skipped within five seconds of starting.
  • More than a third are skipped within 30 seconds.
  • Nearly half of all songs are skipped at some point…

Lamere then broke this down into the last-second-listened frequency. If you’ve made it past the 12th second, you have demonstrated amazing commitment…

Lamere concludes:

“When we are more engaged with our music – we skip more, and when music is in the background such as when we are working or relaxing, we skip less. When we have more free time, such as when we are young, or on the weekends, or home after a day of work, we skip more. That’s when we have more time to pay attention to our music. The big surprise for me is how often we skip.  On average, we skip nearly every other song that we play.”

One interpretation: people simply don’t take much time to decide whether they like a song or not. Those opening seconds are crucial.

A second interpretation: another example of shorter attention spans today. Quickly moving through songs, scanning Internet headlines and viral videos, always have to be entertained…

A third interpretation: services like Spotify make skipping easier. Spotify has over 20 million songs and it is easy to just move on to another track.

A question: It would be interesting, however, to see if people consistently skip the same songs when presented with them – how much of this is dependent on their immediate context versus a skip representing a longer-term dislike for the song? Or, if people had to listen to a song for a longer period of time – like it was playing in a store they were shopping in – would they come to like it?

When anti-government forces can control the public narrative about drone strikes in Yemen

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While social media was praised in helping the Arab Spring movement, the new availability of Twitter in Yemen has changed who gets to control the public narrative about violence:

The result: AQAP and the Yemeni public have left the government far behind in an information war made possible by the spread of the Internet in the Arab world’s poorest nation. Authorities can no longer shape the narrative of counterinsurgency, particularly when it comes to controversial drone strikes…But the number of Internet users in the country increased nearly tenfold between 2010 and 2012, according to government figures, although even with that rapid expansion, less than a quarter of Yemenis have regular internet access.

Most drone strikes, which are believed to be US operations, target the most impoverished and isolated parts of Yemen where AQAP operates. The region’s remoteness plays into the group’s hands; it also makes it easy for the government to suppress any negative information, including civilian casualties from drone strikes and other aerial attacks.

But now Yemenis can easily, quickly share on-the-ground information. Last December, an airstrike targeted a wedding convoy, killing roughly a dozen civilians. The government initially identified the casualties as militants, but locals soon began posting photos of the dead on Facebook and tweeting the names of victims, directly challenging the government’s obfuscation.

Sounds like quite a change in a short amount of time. The availability of the Internet and social media threaten all sorts of traditional institutions that have relied on controlling information. All of the sudden, alternative viewpoints are available and regular citizens can pick and choose which to follow, believe, and propagate.

What does this do for American foreign policy? We generally disapprove of regimes that crack down on Internet availability (think China) but this is usually because we want to get our messages through. What happens when the same technologies are used to counter American narratives?

The factors behind the rise of viral maps

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Here is a short look at how viral maps (“graphic, easy to read, and they make a quick popular point”) are put together by one creator:

When I need to find a particular data set, it’s often as straightforward as a search for the topic with the word “shapefile” or “gis” attached. There’s so much data just sitting on servers that if you can imagine it, it’s probably out there somewhere (often for free). Sometimes though, finding data requires a deeper search. A lot of government-provided data sits inside un-indexed data portals or clearinghouses. Depending on the quality of the portal, these can be tedious to sort through…

Simplicity and ease-of-use: Interactive maps are great, but I want the maps I make to be straightforward to read and understand. I don’t want viewers to have to figure out how to use the map; they should just be able to look at it and figure out what’s going on.

Projections: Typical web maps are limited to the Web Mercator projection. I don’t have any objection to Mercator in principle (in fact it’s brilliant for what it does), but I can’t in good conscience use it for maps at a continental or global scale. Sticking to static maps allows me to choose more appropriate projections for the data and region I’m depicting.

Uniformity: I want everyone who visits my maps to be presented with the same information. I don’t want some algorithm deciding that one visitor is shown a particular view while another visitor gets a different one.

These principles sound similar to what one would expect for any sort of online chart or infographic. There is plenty of data available online but it takes some skill in order to present the data clearly and then market the map to the appropriate audience.

Now that I think about it, it is a little surprising that it took this long for viral maps to catch on. First, the Internet makes a lot of geographic data easily accessible. Two, it is a visual medium and maps are essentially graphics (audio is another story). Third, geographic data seems to feed into a lot of hot-button topics of conversation these days as people of different races (residential segregation), cultural viewpoints (think the American South or the Bible Belt), education (think the Creative Callas looking for exciting urban neighborhoods), and other groupings tend to live in different places.

I wonder if the real story here isn’t the technology that makes mapping on a large-scale relatively easy today. GIS software has been around for a while but it generally pretty expensive and has a learning curve. Now, there are numerous websites that offer access to data and mapping capability (think the Census or Social Explorer). Shapefiles are used by a variety of local governments and researchers and can be downloaded. There are good freeware GIS programs like GeoDa. You need some bandwidth and computing power to get the data and crunch the numbers. All together, the pieces have now come together for more people to access, manipulate, and publish maps in a way that wasn’t possible even just 5 years ago.

 

“A Brief History of Exploding Whales”

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Whales explode due to natural and man-made causes:

Sometimes beached whales erupt on their own, but sometimes humans blow them up first—as was the case in Florence, Oregon, in 1970. The town of Florence may have been the first to confront the dilemma that faces Trout River today.

Oregon officials thought their whale was too big to cut up or burn; they ended up hiring a highway engineer named Paul Thornton, from the state’s transportation department, to devise a plan. Thornton decided on using dynamite to blast the whale to bits. He figured that the blown-up pieces of blubber would scatter into the sea and whatever remained would be scavenged by birds and crabs…

In an obituary for Thornton, who died in October 2013, Elizabeth Chuck of NBC News describes what happened that day:

Bystanders were moved back a quarter of a mile before the blast, but were forced to flee as blubber and huge chunks of whale came raining down on them. Parked cars even further from the scene got smashed by pieces of dead whale. No one was hurt, but the small pieces of whale remains were flecked onto anyone in the area.

Though I wouldn’t have called it such at the time, this is the first “viral video” I remember discovering. And it would be years before it made it to YouTube. I remember in high school stumbling onto a fairly simple HTML page that had a video of this scene in Oregon. The news report was one of the strangest I had ever seen: people gathering to watch and then running as quickly as possible away from an exploding whale. I showed it to a number of people that had never seen anything like it. It isn’t exactly what viral videos are today – which tend to be more pop culture, catchy – but it was certainly unique and something quite foreign to most Midwesterners.

How Google’s driverless car navigates city streets, construction, and urban traffic

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Eric Jaffe provides some info on how driverless cars navigate more complex urban roads:

Boiled down, the Google car goes through six steps to make each decision on the road. The first is to locate itself — broadly in the world via GPS, and more precisely on the street via special maps embedded with detailed data on lane width, traffic light formation, crosswalks, lane curvature, and so on. Urmson says the value of maps is one of the key insights that emerged from the DARPA challenges. They give the car a baseline expectation of its environment; they’re the difference between the car opening its eyes in a completely new place and having some prior idea what’s going on around it.Next the car collects sensor data from its radar, lasers, and cameras. That helps track all the moving parts of a city no map can know about ahead of time. The third step is to classify this information as actual objects that might have an impact on the car’s route — other cars, pedestrians, cyclists, etc. — and to estimate their size, speed, and trajectory. That information then enters a probabilistic prediction model that considers what these objects have been doing and estimates what they will do next. For step five, the car weighs those predictions against its own speed and trajectory and plans its next move.

That leads to the sixth and final step: turning the wheel this much (if at all), and braking or accelerating this much (if at all). It’s the entirety of human progress distilled to two actions…

The Google car is programmed to be the prototype defensive driver on city streets. It won’t go above the speed limit and avoids driving in a blind spot if possible. It gives a wide berth to trucks and construction zones by shifting in its lane, a process called “nudging.” It’s extremely cautious crossing double yellows and won’t cross railroad tracks until the car ahead clears them. It hesitates for a moment after a light turns green, because studies have shown that red-light runners tend to strike just after the signal changes. It turns very slowly in general, accounting for everything in the area, and won’t turn right on red at all — at least for now. Many of the car’s capabilities remain locked in test mode before they’re brought out live.

Quite a process to account for all of the potential variables including other drivers, pedestrians and cyclists, weather conditions, and other objects on the road like construction or double-parked vehicles. I imagine this is some intense code that has to provide a lot of flexibility.

This also reminds me of some of my early experiences driving. It took some time to adapt to everything – watch your speed, check all those mirrors, what are the other cars doing, what is coming up ahead – and I remember wondering how people could even carry on conversations with others in the car while trying to drive. But, with practice and adaptation, driving today seems like second nature. And, I suspect from my own experience that drivers are not 100% vigilant (maybe 80% is more accurate?) while driving as they generally think they have things under control.

All that said, driving is a remarkable cognitive task and replicating this and improving on it in a 100% vigilant system requires lots of work.

NBC: social media use driven by popular TV shows, not the other way around

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The Financial Times reports that after studying media habits related to its Olympic coverage, NBC found less social media activity linked to television broadcasts than might have been expected. In other words, it isn’t apparent that people tune into television programs because they see activity about it on social media. At stake is a lot of advertising money.

It will be interesting to see how this plays out. From its early days, one of the major critiques of television was that it encouraged passivity: people generally sat on the couch in their private homes watching a screen. While they may have had conversations about TV with others (and a lot of this has moved online – just see how many sites have Game of Thrones recaps each week), television watching was a limited social activity practiced alone, with family, or close friends. Whether social media changes this fundamental posture in watching television remains to be seen.

Claim: Airbnb and Lyft increasing social trust amongst Americans

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Social trust in the United States may be declining but one writer argues two new services are providing space where Americans can start trusting a little more:

The sharing economy has come on so quickly and powerfully that regulators and economists are still grappling to understand its impact. But one consequence is already clear: Many of these companies have us engaging in behaviors that would have seemed unthinkably foolhardy as recently as five years ago. We are hopping into strangers’ cars (Lyft, Sidecar, Uber), welcoming them into our spare rooms (Airbnb), dropping our dogs off at their houses (DogVacay, Rover), and eating food in their dining rooms (Feastly). We are letting them rent our cars (RelayRides, Getaround), our boats (Boatbound), our houses (HomeAway), and our power tools (Zilok). We are entrusting complete strangers with our most valuable possessions, our personal experiences—and our very lives. In the process, we are entering a new era of Internet-enabled intimacy.

This is not just an economic breakthrough. It is a cultural one, enabled by a sophisticated series of mechanisms, algorithms, and finely calibrated systems of rewards and punishments. It’s a radical next step for the ­person-to-person marketplace pioneered by eBay: a set of digi­tal tools that enable and encourage us to trust our fellow human beings…

That’s the carrot side of a more intimate economy, the idea that treating people well will result in a better experience. There is a stick side as well: Act badly and you’ll be barred from participat­ing. Nick Grossman, a general manager at Union Square Ventures and a visiting scholar at the MIT Media Lab, says that while Uber drivers are generally positive about the service, he has spoken with some who worry about picking up a ­couple of bad reviews, falling below the acceptable rating threshold, and getting fired. (The same holds for passengers: Manit, the Lyft driver, says she won’t pick up anyone with less than a 4.3-star rating.) “There’s a legitimate question: How do we feel about living in an environment of hyper-accountability?” Grossman asks. “It’s very effective at producing certain outcomes. It’s also very Darwinian.” Just like resi­dents of pre-industrial America, sharing-economy participants know that every transaction contributes to a reputation that will follow them, potentially for the rest of their lives.

Two things seem critical to increasing social trust in these systems:

1. The willingness of enough Americans to trust technology to solve problems and be willing to serve as early adopters who work the kinks out of this system. As the article notes, some users have been burned. But, this then gives each service a chance to respond and get it right in the future.

2. These services provide enough guidelines to help people feel safe. This is quite different from stories in recent years about sharing within a neighborhood or a barter system. Those rely on face-to-face interaction, often with people with whom one could expect to have future interactions. These services provide mediated interaction that leads to some face-to-face interaction. The long-term effects of mediated interaction (this is also what social media tends to offer) might be quite different.