Informationized

‘Following’ News

2010-06-24T11:25:45Z

As usual, the latest Pew Internet study on participation in news is loaded with great data and insights. This part in particular jumped out at me:

…23% of the social networking users who get news online say they specifically get news from news organizations and individual journalists they follow in the social networking space. In other words, they have friended or become a fan of a journalist or news organization and they catch up on news through this relatively new channel of news dissemination. That amounts to 13% of all internet users.

via News as a social activity | Pew Internet & American Life Project.

Given my previous thoughts on following journalists, I’d be very curious to see a breakdown of followers between news organizations and journalists. I suspect official news organization feeds account for more followers than the journalists that work for them but I could easily be wrong. I’d be even more curious to how it has changed in the past year.

Sentiment in Blog Memes

2010-02-17T20:07:03Z

This post is part of a series on corporate blogs based on data collected for my Masters thesis and it focuses on sentiment in blog memes.

All 1,553 consumer blog posts captured by the study were tested individually and the result was a statistically significant skew towards positive sentiment. The chart below shows that 887 or 57.1% percent of posts were demonstrated positive sentiment. A further 33.4% of posts expressed neutral sentiment and just 9.5% of posts were negative.

Pearson’s Chi-Square test was used to determine if the skew towards positive sentiment was statistically significant. It was based on the assumption that if there was no bias, the expected result would be an equal distribution of posts in all three sentiment categories. The test showed that the observed result was different enough from the expected result that it represented a statistically significant bias towards positive sentiment in the data.

A positive bias among consumers responding to corporate blog posts creates some tension with research that suggests consumers do not trust corporate blogs. But, as social media becomes increasingly distributed, this becomes an increasingly irrelevant debate. Although, even if it is the case, corporate blogs serve other purposes.

Corporations are taking social media seriously and there are already numerous small companies creating tools to monitor online chatter, including sentiment, across multiple platforms and most include tools for companies to interact in these streams as well.

Sentiment seems to be a particularly alluring area and one that currently appears to be reaching a wider audience, but its viability remains passionately debated. Demand stems from a view of social media as a channel for customer interaction and word-of-mouth. And it results in a broad cross-section of potential uses for companies and professional company watchers in marketing and PR, finance, law, media, consulting, academia and more.

The sentiment data for this study was produced by the Parnassus Group, a social media research firm, using a custom configuration of their Sentimine tool. All articles were given a single sentiment score at the document level without targeting any particular topic or entity such as companies, products or brands.

In the next post in this series, I’ll talk more about sentiment among early posts in memes and the most connected posts in memes, which were the primary variables of my study.

Power Laws in Blog Memes

2009-10-25T02:03:22Z

This is post is part of an ongoing series on corporate blogs based on data I collected for my Masters thesis. It’s been a while since I last posted in this series and when I was writing the last post I realized how difficult it was to describe any one cut of data in isolation. For these reasons, I wanted to provide a recap of the previous few posts on the size and structure of blog memes before moving on to my findings on sentiment.

In an ideal world, I would have liked to have created something more visual but here is the time-limited version:

389 Fortune 500 corporate blogs were studied and they produced 5,887 posts in the two-month data collection period.

The top three companies, Google, HP, and Yahoo accounted for more than a third of the 389 blogs.

21% of the 389 corporate blogs did not post at all in the two-months. Almost half (49%) posted no more than 5 times.

Only 299 (5%) of the 5,887 corporate posts produced memes as they were measured for my study.

Only 14 Fortune 500 companies out of the 76 that used blogs produced memes and most were in technology-related industries.

The most active company, Google, accounted for almost half of memes by itself.

The most connected blog post had 17 incoming links from other posts but 89% had one or none.

The largest meme reached 56 posts but 88% of memes contained no more than ten. Just over half of these memes were comprised of the minimum two posts, and 240 out of 299 were only two tiers deep.

There were 792 distinct blogs found participating in memes, but 79% only appeared once and 95% appeared no more than three times.

This little recap is a long way of saying that power laws were present in most cuts of the data. The presence of power laws in social networks has been known for some time and this data represents another example.

It makes analyzing the data for patterns more complex, but potentially more rewarding, than data that follows a normal (bell-curve) distribution and there are plenty of much smarter people working on ways to do that.

Next Up For Disruption? College – Techdirt

2009-10-01T22:04:47Z

Testing the Press This bookmarklet for Wordpress with this nice line from Mike Masnick this morning:

True disruptive innovation is never about just moving a legacy model to a new medium, but about embracing some aspect of that new medium to offer something in a different way that really wasn’t possible prior to that.

via Next Up For Disruption? College – Techdirt.

Networks: A Fundamentally Different Exchange

2010-03-02T22:02:22Z

Last month, Brad Burnham of Union Square Ventures wrote this about ‘free’ Web services:

Free is not a pricing strategy, a marketing strategy, or the inevitable consequence of a market with low variable costs…

Services are not offered for free at all. There is an exchange of value between users, the creators of the raw material – data, content, and meta-data, and the network where that data is converted into insight.

I’ve written before that ‘free’ a marketing strategy rather than a business model but that is quite clearly inaccurate or at least incomplete (and I’ve realized my error). Brad sees beyond our traditional understanding of sellers providing services to individual buyers, individually.

Lots of Web services connect users to one another to create networked services. In these cases, the relationship between buyers and sellers has been fundamentally changed to something more like infrastructure/context providers and data contributors.

It means that not all ‘free’ is created equal. Free trials, cross-subsidies, free content and even free Web services targeted at individuals, individually, are completely different to free services that result in networks. Without a network, free is just marketing. It’s an expense incurred by a company in order to generate revenue some other way within the existing framework of buyers and sellers.

In contrast, free services that are designed to connect users to one another and build networks do not operate within that existing framework. Users contribute data for their own utility but also, and perhaps more importantly, in exchange for access to the network – the data provided by other users.

For every additional user that joins a network, the value of the service increases for everyone else. A byproduct of networks is that they also seem to produce something new, interesting and hopefully valuable at the center, often based on aggregated user data, actions, gestures or behaviors.

In these cases, free is clearly not an enticement to use a service. It is marketing in the sense that it involves a price – free – but I think free is the market price for contribution, probably because it creates the least friction. I’m not sure it has anything to do with falling marginal costs.

The difference between free networks and free stuff may offer a fresh perspective on the turbulence in content industries like music and news. For example, it could be argued that users want ‘free’ as in networks but publishers only see ‘free’ as in stuff.

Within the traditional framework of buyers and sellers, free content is a giveaway and unlicensed use of content is piracy. But, I’d argue that users don’t expect to get ‘free stuff’ online. Instead, with all the social tools now at their disposal, they want to alter the exchange altogether.

If there is a problem with offering free content online it’s that publishers are not capturing the other side of the exchange, which in this case, is providing an infrastructure and a context around which networks can form.