find all the relevant points of view on a topic, and especially to focus attention on those that bring the most new information — such as arguments one hasn't heard before, or arguments that counter one's own. Arguments given in deletion discussions may involve facts sourced to an external reference (“his status is `Active’”); assertions of the appropriate policy to apply (“baseball notability guidelines”); references to specific criteria (“Have appeared in at least one game in … any other top-level national league”) and interpretations (“I feel he qualifies”). Existing work on templating arguments takes the form of argument schemes; 60 types of arguments have been identified and classified . The `argument from rules’ type best fits the `typical argument’ shown to the left. Particular argument schemes appear with various frequencies in deletion discussions, and not all types of arguments meet community standards. For example, arguments `from popular opinion’, and `from position to know’ (i.e. sourced to personal knowledge) are not given credence. Value-based arguments (e.g. `from waste’ or `from sunk costs’) are sometimes effective, yet are not decisive: they are mainly supplemental.
Digital Enterprise Research Institute Building a Standpoints Web to Support Decision-Making in Wikipedia Jodi Schneider Argument Exploration Wikipedia Deletion Discussion Argument exploration is joint work with the University of Liverpool, Adam Wyner, Katie Atkinson & Trevor Bench-Capon. Thanks to a COST Short-term scientific mission (STSM 1868) from the COST Action ICO801 on Agreement Technologies! Summarizing Standpoints Support 3 groups:[Delete the article]...hasnt played 1. Newcomerssince 2008. His 66-73 record is Learn effective argument & rhetoricfar from stellar and, in myopinion, does not merit an article. • Administrators Determine outcomes>>He pitched last month andplays for the Venezuelan League. • Readers Revisiting DiscussionsThis meets our article criteria. Understand the deciding factors Using Standpoints Abstract Although the Web enables large-scale collaboration, its potential to support group decision-making has not been fully exploited. My research aims to analyze, extract, and represent disagreement in purposeful social web conversations. This supports decision-making in distributed groups by representing individuals claims and their justifications in a "Standpoints Web", a hypertext web interlinking the claims and justifications made throughout the social web. The two main contributions of my dissertation are an architecture for the Standpoints Web and a case study implementing the Standpoints Web for Wikipedias deletion discussions. Enabling Networked Knowledge Main Ph.D. funding: Science Foundation Ireland Grant No. SFI/08/CE/I1380 (Líon-2) Totten image credit: http://cuentacompleta.files.wordpress.com/2011/09/5229630.jpg