"social media" entries

If followers can sponsor updates on Facebook, social advertising has a new horizon

The frequency of sponsored posts looks set to grow.

This week, I found that one of my Facebook updates received significantly more attention that others I’ve posted. On the one hand, it was a share of an important New York Times story focusing on the first time a baby was cured of HIV. But I discovered something that went beyond the story itself: someone who was not my friend had paid to sponsor one of my posts.

Promoted post on Facebook.

According to Facebook, the promoted post had 27 times as many views because it was sponsored this way, with 96% of the views coming through the sponsored version.

When I started to investigate what had happened, I learned that I’d missed some relevant news last month. Facebook had announced that users would be able to promote the posts of friends. My situation, however, was clearly different: Christine Harris, the sponsor of my post, is not my friend.

When I followed up with Elisabeth Diana, Facebook’s advertising communications manager, she said this was part of the cross-promote feature that Facebook rolled out. If a reporter posts a public update to his followers on Facebook, Diana explained to me in an email, that update can be promoted and “boosted” to the reporter’s friends.

While I couldn’t find Harris on Facebook, Diana said with “some certainty” that she was my follower, “in order to have seen your content.” Harris definitely isn’t my friend, and while she may well be one of my followers, I have no way to search them to determine whether that’s so. Read more…

Four short links: 22 February 2013

Four short links: 22 February 2013

Indiepocalypse Continued, Unblockable p2p Twitter, Disposable Satellites, and iOS to HTML5

  1. Indiepocalypse: Harlem Shake Edition (Andy Baio) — “After four weeks topping the Billboard Hot 100, Macklemore and Ryan Lewis’s “Thrift Shop” was replaced this week by Baauer’s “Harlem Shake,” the song that inspired the Internet meme.”
  2. SplinterNet — an Android app designed to create an unblockable Twitter like network that uses no cellular or Internet communications. All messages are transmitted over Bluetooth between users, creating a true peer-to-peer messaging system. All messages are anonymous to prevent retaliation by government authorities. (via Ushahidi)
  3. Disposable Satellites (Forbes) — “tiny, near-disposable satellites for use in getting battlefield surveillance quickly […] launched from a jet into orbit, and within a few minutes […] provide soldiers on the ground with a zoomed-in, birds-eye view of the battlefield. Those image would be transmitted to current communications devices, and the company is working to develop a way to transmit them to smartphones, as well.”
  4. Native iOS to HTML5 Porting Tool (Intel) — essentially a source-to-source translator that can handle a number of conversions from Objective-C into JavaScript/HTML5 including the translation of APIs calls. A number of open source projects are used as foundation for the conversion including a modified version of Clang front-end, LayerD framework and jQuery Mobile for widgets rendering in the translated source code. A porting aid, not a complete translator but a lot of the dog work is done. Requires one convert to Microsoft tools, however. (via Kevin Marks)

Fruit or mobile device: learning concepts through connections

Preview of insights shared at upcoming session at Strata Santa Clara

Social media gives us the power to share content and engage with a wide range of internet users. As a person or brand, we are often concerned with who we are talking to and how we can better serve our viewers. Traditional demographics such as ‘female’ and ‘25-30’ are no longer sufficient in this arena. For example, Google is having a hard time getting gender and age correct for ad preferences. It is more interesting to observe what content is consumed and how attention changes over time.

Bitly, which is used to shorten and share links, can offer insight into this space. This means the data has an unprecedented view into what people are sharing and has a holistic view of what users are concerned about on the internet.

We use their data to look into how we can define the audience of different content. The simplest example of this is: given a group of users that click on “oreilly.com”, what other websites do they engage with. We now have what bitly calls a co-click graph. Domains are represented as nodes while edges between nodes represent the number of people that have clicked on each domain. A co-click graph can be made to represent any number of attributes, but for now we are going to remain interested in topics and keywords.

ASmithFig1

Read more…

Public health case study: Tracking zombies and vampires using social media

Preview of Strata Santa Clara 2013 Session

Towards the end of 2012, a battle that the pitted state versus state, father versus son, wife versus Bunco group, dog versus cat, finally reached a truce spawned by the treaty we all sign every fours years known as the presidential election. While the death match between red versus blue states has finally faded from our televisions and twitter feeds, we can now focus on the real issues of the day.

Longer then Romney’s candidacy bid for the white house, there has been a war going on in America, an undeath match of sorts between Zombies and Vampires. Like a flu pandemic sweeping the nation, the undead have been infiltrating our lives in every aspect. What traditionally was only a mild outbreak in October has turned into a year round epidemic that our society cannot seem to shake.

Read more…

Four short links: 18 February 2013

Four short links: 18 February 2013

Social Aggregator, Social Tracking, Data Boom, and Vim Search

  1. crowy — open source social media aggregator.
  2. Raytheon makes Social Media Tracking Software (Guardian) — the technology was shared with US government and industry as part of a joint research and development effort, in 2010, to help build a national security system capable of analysing “trillions of entities” from cyberspace.
  3. Big Data Leads to Jobs for ClevelandSpun out of the Cleveland Clinic three years ago, Explorys already employs 85 people and the prospects are as bright as its hip new offices in University Circle. Suddenly, economic development specialists are eyeing Big Data, and its potential for Cleveland, with new intensity. From rust belt to Hadoop uber alles.
  4. YouCompleteMea fuzzy search engine for Vim.
Four short links: 10 January 2013

Four short links: 10 January 2013

Engineering Virality, App Store Numbers, App Store Data, and FPGA OS

  1. How To Make That One Thing Go Viral (Slideshare) — excellent points about headline writing (takes 25 to find the one that works), shareability (your audience has to click and share, then it’s whether THEIR audience clicks on it), and A/B testing (they talk about what they learned doing it ruthlessly).
  2. A More Complete Picture of the iTunes Economy — $12B/yr gross revenue through it, costs about $3.5B/yr to operate, revenue has grown at a ~35% compounded rate over last four years, non-app media 2/3 sales but growing slower than app sales. Lots of graphs!
  3. Visualizing the iOS App Store — interactive exploration of app store sales data.
  4. BORPHan Operating System designed for FPGA-based reconfigurable computers. It is an extended version of the Linux kernel that handles FPGAs as if they were CPUs. BORPH introduces the concept of a ‘hardware process’, which is a hardware design that runs on an FPGA but behaves just like a normal user program. The BORPH kernel provides standard system services, such as file system access to hardware processes, allowing them to communicate with the rest of the system easily and systematically. The name is an acronym for “Berkeley Operating system for ReProgrammable Hardware”.
Four short links: 3 January 2013

Four short links: 3 January 2013

Historic Social Media, Latency Numbers, Quantified Auto, and I Feel Old

  1. Community Memory (Wired) — In the early 1970s, Efrem Lipkin, Mark Szpakowski and Lee Felsenstein set up a series of these terminals around San Francisco and Berkeley, providing access to an electronic bulletin board housed by a XDS-940 mainframe computer. This started out as a social experiment to see if people would be willing to share via computer — a kind of “information flea market,” a “communication system which allows people to make contact with each other on the basis of mutually expressed interest,” according to a brochure from the time. What evolved was a proto-Facebook-Twitter-Yelp-Craigslist-esque database filled with searchable roommate-wanted and for-sale items ads, restaurant recommendations, and, well, status updates, complete with graphics and social commentary. But did it have retargeted ads, promoted tweets, and opt-in messages from partners? I THOUGHT NOT. (via BoingBoing)
  2. Latency Numbers Every Programmer Should Know (EECS Berkeley) — exactly that. I was always impressed by Artur Bergman’s familiarity with the speed of packets across switches, RAM cache misses, and HDD mean seek times. Now you can be that impressive person.
  3. Feds Requiring Black Boxes in All Vehicles (Wired) — [Q]uestions remain about the black boxes and data. Among them, how long should a black box retain event data, who owns the data, can a motorist turn off the black box and can the authorities get the data without a warrant. This is starting as regulatory compliance, but should be seized as an opportunity to have a quantified self.
  4. Average Age of StackExchange Users by Tag (Brian Bondy) — no tag is associated with people who have a mean age over 30. Did I miss the plague that wiped out all the programmers over the age of 30? Or does age bring with it supreme knowledge so that old people like me never have to use StackExchange? Yes, that must be it. *cough*

Saving publishing, one tweet at a time

Helping both readers and writers look good on social media.

Traffic comes to online publishers in two ways: search and social. Because of this, writing for the tweet is a new discipline every writer and editor must learn. You’re not ready to publish until you find the well crafted headline that fits in 100 characters or so, and pick an image that looks great shared at thumbnail size on Facebook and LinkedIn.

But what of us, the intelligent reader? Nobody wants to look like a retweet bot for publishers. The retweet allows us no space to say why we ourselves liked an article.

Those of us with time to dedicate are familiar with crafting our own awkward commentaries: “gr8 insight in2 state of mob,” “saw ths tlk last Feb,” “govt fell off fiscal clf”. Most of the time it’s easier just to bookmark, or hit “read later,” and not put in the effort to share.

Rescue is at hand. The writer and programmer Paul Ford has created a bookmarklet, entitled Save Publishing. On activating the bookmarklet while viewing an article you wish to share, it highlights and makes clickable all the tweetable phrases from the page. Read more…

Big, open and more networked than ever: 10 trends from 2012

Social media, open source in government, open mapping and other trends that mattered this year.

In 2012, technology-accelerated change around the world was accelerated by the wave of social media, data and mobile devices. In this year in review, I look back at some of the stories that mattered here at Radar and look ahead to what’s in store for 2013.

Below, you’ll find 10 trends that held my interest in 2012. This is by no means a comprehensive account of “everything that mattered in the past year” — try The Economist’s account of the world in 2012 or The Atlantic’s 2012 in review or Popular Science’s “year in ideas” if you’re hungry for that perspective — but I hope you’ll find something new to think about as 2013 draws near. Read more…

Why isn’t social media more like real life?

You know the graph. Use it to provide a more human experience.

I finally got around to looking at my personal network graph on Linkedin Labs the other day. It was a fun exercise and I got at least one interesting insight from it.

Take a look at these two well defined and distinct clusters in my graph. These are my connections with the startup I worked for (blue) and the company that acquired us in 2008 (orange). It is fascinating to me that all these years later the clusters remain so disconnected. There are shared connections within a common customer base, but very few direct connections across the clusters. I would love to see maps from some of my other colleagues who are still there to see if theirs show the same degree of separation. This was an acquisition that never really seemed to click and whether this is a picture of cause or effect, it maps to my experiences living in it.

That’s an aside though. What this graph really puts in stark relief is what every social network out there is learning about us. And this graph doesn’t really tell the whole story because it doesn’t represent edge weights and types, which they also know. Social networks know who we connect with, who we interact with, and the form and strength of those interactions.

But this post isn’t a privacy rant. I know they know this stuff and so do you. What this image got me thinking about again is why social networks aren’t using this information to create for us a social experience that is more like our real world, and frankly more in tune with our human-ness. Read more…