Category Archives: Business

Half of iPhone users access social networking from their mobile

Posted on by
Reply

There is no doubt that social networking has become the phenomenon of the age. It has moved forward with such a pace that users have probably out stripped technology in terms of the number of applications available. Many of the applications available for the iPhone have connectivity to networks such as Facebook and Twitter, but many have only a limited range of functions when compared to the main networks. The iPhone has shown itself to be uniquely placed to move telephone networking forward; however, the applications available do not help it to be fully integrated into the wider world of social networking.

Few of the applications available are ideal. Many of them have limited functions which only work locally, so it is up to the user in the end to choose an application which is going to be of most use to them. Some of the applications, such as Bluepulse are fairly simple applications which are simple and fast, but lack many of the functions users of Facebook and Twitter are used to. Although it has the appearance of a web page, with friends, messaging and status updates, that is about all the application has to offer. Facebook has an application itself, which although functional, is inferior to the real thing. It has e-mail recognition and integrated chat; however the applicati0n does not run in the background which means you have to be logged in. This means that e-mail and chat are not active all the time. The application does not have location awareness, which some of the other applications have. Another application which demonstrates the wide variation in functionality is iFob. This application is fine if you are within a reasonably close proximity, so great if you are in a concert or bar, and may be useful for business networking events. However, you cannot add friends and can only be used locally.

Loopt is an application which has Twitter and Facebook integration, although actually linking up with Facebook friends is not all that easy. People profiles are fairly simple with just a name and picture. Twitterlator may be one of the better applications for Twitter users. With full search and full friend functionality as well as camera, and location integration, it also has an emergency button which can use to alert friends. However this application can be slow at times and still does not run in the background.

There is no doubt that there is huge potential for social networking applications, and companies are probably still at the stage where we are gathering information. There are a number of business networks starting to spring up which will link people with similar status or positions within companies so that ideas can be exchanged. Almost fifty per cent of iPhone users access social networking sites on iPhone, which is almost twelve times the market average, so the phone and it`s demographic are ideally placed for a bright future in social networking. For up to date iPhone news, go to apple iphone

HP Labs report predicting content popularity, & thus revenue

Posted on by
Reply

After picking up on HP Labs research on the value of paying attention to top contributors I thought it would be interesting to check previous research from the same guys at Palo Alto, looking at predicting the popularity of online content (pdf) or read it on scribd). The abstract nicely sums it up. Could be useful for planning a community growth strategy for example:

We present a method for accurately predicting the long time popularity of online content from early measurements of user’s access. Using two content sharing portals, Youtube and Digg, we show that by modeling the accrual of views and votes on content offered by these services we can predict the long-term dynamics of individual submissions from initial data.

“In the case of Digg, measuring access to given stories during the first two hours allows us to forecast their popularity 30 days ahead with remarkable accuracy, while downloads of Youtube videos need to be followed for 10 days to attain the same performance. The differing time scales of the predictions are shown to be due to differences in how content is consumed on the two portals: Digg stories quickly become outdated, while Youtube videos are still found long after they are initially submitted to the portal. We show that predictions are more accurate for submissions for which attention decays quickly, whereas predictions for evergreen content will be prone to larger errors.

So let’s get down to the bullet points:

  • There is a linear relationship between the time it takes to consume contributor generated content, and the ability to predict it.
  • There is a clear asymmetrical relationship at work — a few get a lot of attention. A ranking or rating mechanism supports this feature as the ‘rich get richer’.
  • As a side observation only 3% of YouTube views come from incoming links. I assume that includes embedded videos on blogs for example, but that’s not clearly stated.
  • The social network feature of Digg is key as fans get updates of what their favourite folk are reading and follow suit.
  • There is a key difference between Digg and YouTube popularity patterns related to the content context. Digg content is news-related often and soon as such reaches its ‘sell by date’. In contrast on YouTube videos are not promoted to the frontpage in the same way as Digg, and members find the content largely through the search: “An important difference that is apparent in the figure is that while Digg stories saturate fairly quickly (in about
    one day) to their respective reference popularities, Youtube videos keep getting views all throughout their lifetime (at least throughout the data collection period, but it is expected that the trendline continues almost linearly). The rate at which videos keep getting views may naturally differ among videos: less popular videos in the beginning are likely to show a slow pace over longer time scales, too.”
  • Another side observation: it matters what time of day you post content to Digg, if it’s posted in the middle of the night for majority of US readers then this will have an impact. I guess this is a general reminder of making sure content uploads on global communities take account of the various needs of readers, particularly to make sure they are wide awake when content goes up!
  • Digg itself may not be perfect in promoting content. It promotes on average 11% of content which does not generate sustained interest. Guess this means we are all on a learning curve;-)
  • The maths supports the ‘more popular content is early on, the more it will be later on’ rule of thumb:

Popularity measures

  • The researchers provides 3 models to predict submission’s popularity as a time in the future. They favour the constant scaling model (CS) for relative measures, while the linear model (LN) for absolute measures. In conclusion they suggest the error is less using the relative measure.

My reading of their results is that relative measures are particularly useful for judging the revenue value of advertisements placed next to content, but not so good for content popularity. Which is good for YouTube’s advertisers, but bad news in helping Digg correct its 11% error in promoting content which in fact turns out not to be popular!

I guess this also supports my conclusion from the previous post that (1) Have a strategy to support your top contributors. (2) As part of this measurable strategy make sure the means for them to gain attention work well. As I believe my sister company Sift Media does, you can then further tie the attention scalar by tying attention to payment to further reinforce this strategy’s influence.