Web 2 0 and Collective Intelligence Mark Levene

Web 2. 0 and Collective Intelligence Mark Levene (Follow the links to learn more!)

Web 2. 0 Technologies • Empowering users! • Users can create, edit, modify, share, link to and tag content • Examples: Delicious, Flickr, Facebook, Digg, Twitter, Wikipedia, Ebay and You. Tube • Technologies: Ajax, RSS, Open Ap. Is, Widgets, Mashups, SAAS, • The Machine is Us/ing Us

Social Tagging and Bookmarking • • Tag your photos (Flickr) Tag your videos (You. Tube) Tag web pages (Delicious) Folksonomy vs Taxonomy • Tag clouds – Wordle • Search with tags - My. Taggy

Opinion Mining • Online shoppers are influenced by product reviews and are willing to pay more for products highly rated by other consumers. • OM and sentiment analysis mines for options in user generated content. • OM goes beyond Comparison Shopping. • OM can be treated as a classification problem.

Collective Intelligence • The emergence of new ideas as a result of a group effort. • Collaborative filtering and opinion mining are examples of machine technologies. • Wikis and Community Question Answering as example of human-based technologies. • Crowdsourcing is the activity of outscourcing a problem to a large group of people; e. g. Amazon’s Mechnical Turk

Wikipedia – The World’s Largest Encyclopaedia • Has over 14 million articles in 272 languages; the English version has over 3 million articles and could grow to 10 million by 2025. • Wikipedia is very popular, and its elaborate mechanisms ensure quality despite articles not necessarily written by experts.

Ebay – The World’s Largest Online Trading Community • Handles an enormous volume of content, with over 80 million active users, trading $60 billion per year, 120 million items for sale in 50, 000 categories and over 2 billion pageviews per day. • Has a simple auction mechanism, based on a second price auction, where the winner pays the second highest price bid plus a minimum bid increment. • Susceptible to sniping, i. e. last minute bidding (allowed) and shilling, i. e. introducing fake bids to increase the final price (fraudulent).