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Diversity toolkit
 

Diversity toolkit

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Tutorial at the RENDER Kick-off Meeting

Tutorial at the RENDER Kick-off Meeting

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    Diversity toolkit Diversity toolkit Presentation Transcript

    • WP4: Diversity toolkitWP introduction and planning
    • Project overviewWPs 6: Dissemination, exploitation, community WP5: Case studies WP7: Project management WP4: Diversity toolkit Media Wiki Yammer WordPress Google Wave WP3: Diversity representation &processing building Models and Search, selection Presentation Summarization metaphors and ranking and interfaces WP2: Diversity mining Opinion Multilinguality Bias in media Fact coverage Story links detection WP1: Data collection and management Annotation, integration, Blogs News Twitter Wikipedia LOD linking
    • WP Overviewo 2 Taskso T4.1: Extensions to Web 2.0 based collaboration platforms • One deliverable at end of each project yearo T4.2: Best practices (M18-M36) • One deliverable at end of second and third year each
    • T4.1: Extensions to existing toolso First set of extensions, including WordPress and MediaWikio Evaluation of candidates at M12 for further toolso Candidates: Google Wave and Microbloggingo Based on expected impact and case study needs (especially Telefónica) • Which ones would that be?
    • WordPresso Most popular CMS in use todayo Used by 12% of the top 100k Websiteso 25 Mio+ installationso Grew from a blogging systemso Full-fledged CMS by nowo Huge amounts of extensionso PHPo GPL
    • MediaWikio Most popular wiki on the Web todayo Developed for Wikipedia, but was generalizedo Still geared towards high performanceo More than 1000 extensions, like Semantic MediaWikio PHPo GPL
    • Scenario brainstorm ITarget: Bloggers as early adopterso Add links to related, but different opinions Requirements:• Topic discovery on the blog item• Opinion / Bias detection on the item• Finding items on the same topic with different opinions
    • Scenario brainstorm IITarget: Wiki-editingo Check referenced sources • For every source, check how it is biased • Find how many sources are biased in order to predict the bias of the overall article • Evaluate if the source bias translates to content biaso Discover editor bias • To what group of bias does an editor belong to • Does past behavior predict future behavior?
    • Scenario brainstorm IIITarget: Semantic MediaWiki and diversityo Shortipedia (demo)o Anyone can claim anything about anything, but sourceo Mark up source with the exact place in the text for the claim • Train learning • Discovering user bias and bias history of an article • evaluating if a claim still is sourcedo Representations for sourced claims • Reification, name graph?
    • Scenario brainstorm IVTarget: Accessing Forum informationo Access for Telefónicao Discover Hotspots in Forum discussionso Discover interestingness of singular postings in order to guide the user for reading