The article covers the topics Intelligent Web, Openness, Interoperability, A Global Database, 3D Web & Beyond, Control of Information, and Semantic Web versus Web 3.0.

Cho concludes:

Nova Spivack’s Twine is one of the first online services to use Web 3.0 technologies. Its goal is to organize, share and discover information about a user’s interests in networks of like-minded people. Using semantic technologies, and powered by semantic understanding, Twine automatically organizes information, learns about users’ specific interests and makes recommendations. The more users use Twine, the better the service gets to know its users and the more useful it becomes. Twine is an example of Web 3.0 at work, combining the social elements of Web 2.0 with user-specific Semantic Web tools.

http://internet.suite101.com/article.cfm/what_is_web_30

The rise of social media such as blogs and social networks has fuelled interest in sentiment analysis. With the proliferation of reviews, ratings, recommendations and other forms of online expression, online opinion has turned into a kind of virtual currency for businesses looking to market their products, identify new opportunities and manage their reputations. As businesses look to automate the process of filtering out the noise, understanding the conversations, identifying the relevant content and actioning it appropriately, many are now looking to the field of sentiment analysis. If web 2.0 was all about democratizing publishing, then the next stage of the web may well be based on democratizing data mining of all that content that’s getting published.

The problem is that most sentiment analysis algorithms rely on us using simple terms to express our sentiment about a product or service. However, cultural factors, linguistic nuances and differing contexts make it extremely difficult to turn a string of written text into a simple pro or con sentiment. The fact that humans often disagree on the sentiment of text illustrates how big a task it is for computers to get this right. The shorter the string of text, the harder it becomes.

Some experts believe that the key to accurate sentiment analysis is accurate text analysis. Rather than relying on counting ‘good’ or ‘bad’ words that appear across an entire text, this approach uses a deep syntactic analysis of each and every word. OpenAmplify is one such example, which has opened an online developer community for collaboration and innovation related to the semantic web. It is the only generally available web service that can identify sentiment and guidance from text. As such, it is allowing open access to its patented natural language processing technology (NLP).

http://en.wikipedia.org/wiki/Sentiment_analysis#Sentiment_analysis_and_Web_3.0

“People keep asking what Web 3.0 is. I think maybe when you’ve got an overlay of scalable vector graphics – everything rippling and folding and looking misty — on Web 2.0 and access to a semantic Web integrated across a huge space of data, you’ll have access to an unbelievable data resource.”

– Tim Berners-Lee, 2006

http://en.wikipedia.org/wiki/Semantic_Web#Web_3.0

http://www.nytimes.com/2006/05/23/technology/23iht-web.html?_r=1

Stefan D. Schmollack

Hello,

my name is Stefan Schmollack and today I have started this Weblog at NextGenerationWeb.Net about the Next Generation of the Internet, Web 2.0, Web 3.0, and the Evolution of the Internet.

Yours sincerely,

Stefan D. Schmollack

Stefan Schmollack Consulting

http://schmollack.net/