Talking is (virtual) work -supporting online argumentation--2013-09-18 Malta virtual work
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Talking is (virtual) work -supporting online argumentation--2013-09-18 Malta virtual work

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In open collaboration systems, work gets done through talking. We support a particular kind of talk-based work -- deletion discussions in Wikipedia -- by categorizing and summarizing discussions. In a ...

In open collaboration systems, work gets done through talking. We support a particular kind of talk-based work -- deletion discussions in Wikipedia -- by categorizing and summarizing discussions. In a user test, 84% find benefit from this.

This talk about my thesis was given 2013-09-18 in Malta at the Virtual Work training school:
http://dynamicsofvirtualwork.com/malta-training-school/
part of the COST action on Virtual Work
http://cost.eu/domains_actions/isch/Actions/IS1202

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  • http://www.contentwire.com/img/zPEAXe6Ec-soFKmr.jpghttp://www.google.com.mt/imgres?safe=off&hl=en&biw=1024&bih=571&tbm=isch&tbnid=xZxsbu4u3puYRM:&imgrefurl=https://plus.google.com/101764199159921388632&docid=Oa38elmbOUqkBM&imgurl=https://lh3.googleusercontent.com/-g_3CKS9d2Y4/T_NocbZKNKI/AAAAAAAAACg/fZ1SoO3L_7g/s0-d/business_meeting.jpg&w=812&h=300&ei=DKA5UubxMorStAa05ICIBw&zoom=1&iact=rc&dur=94&page=6&tbnh=131&tbnw=217&start=85&ndsp=19&ved=1t:429,r:94,s:0,i:368&tx=100&ty=59
  • written arguments and opinionsanyone can participate
  • “An online environment that supports the collective production of an artifact through a technologically mediated collaboration platform that presents a low barrier to entry and exit, andsupports the emergence of persistent but malleable social structures.”(Forte and Lampe 2013)
  • Summarising my research to dateSkills, knowledge and track record I can bring to Understand & improve online discussions Enabling reuse of arguments and opinions from online social disputes
  • 1“only 0.6 percent of those whose articles are met with deletion stayed editing, compared to 4.4 percent of the users whose articles remained”, http://enwp.org/Wikipedia:Wikipedia_ Signpost/2011-04-04/Editor_retention
  • Mentoring in discussions is effective: Article creators who receive mentoring seem toMake more edits to the articleContinue editingIncrease understanding of policy
  • Experts argue from precedentNovices: values, analogy, cause to effectJodi Schneider, KrystianSamp, Alexandre Passant, and Stefan Decker. Arguments about Deletion: How Experience Improves the Acceptability of Arguments in Ad-hoc Online Task Groups. Computer-Supported Cooperative Work and Social Computing (CSCW 2013).
  • 500 discussions per week about deleting borderline articles
  • 20 novice participants used both systems“The ability to navigate the comments made it a bit easier to filter my mind set and to come to a conclusion.”“summarise and, at the same time, evaluate which factor should be considered determinant for the final decision”
  • Different users are persuaded by different kinds of information. Therefore, to solve peoples’ problems, based on knowledge bases, when dealing with inconsistency, understanding the purposes and goals that people have would be useful. Therefore, the goals of a particular dialogue also matter. These have been considered in argumentation theory: Walton & Krabbe have categorized dialogue types based on the initial situation, participant’s goal, and the goal of the dialogue [11]. The types they distinguish are inquiry, discovery, information seeking, deliberation, persuasion, negotiation and eristic. These are abstractions–any single conversation moves through various dialogue types. For example, a deliberation may be paused in order to delve into information seeking, then resumed once the needed information has been obtained. Higher level context would also be useful: different amounts of certainty are needed for different purposes. Some of that is inherent in a task: Reasoning about what kind of medical treatment to seek for a long-term illness, based on PatientsLikeMe, requires more certainty than deciding what to buy based on product reviews. Informal language is very typically found in social media. Generic language processing issues, with misspellings and abbreviations, slang, language mixing emoticons, and unusual use of punctuation, must be resolved in order to enable text mining (and subsequently argumentation mining) on informal language. Indirect forms of speech, such as sarcasm, irony, and innuendo, are also common. A step-by-step approach, focusing first on what can be handled, is necessary. Another aspect of the informality is that much information is left implicit. Therefore, inferring from context is essential. Elliptical statements require us to infer common world knowledge, and connecting to existing knowledge bases will be needed. We apply sentiment techniques to provide candidates for argumentation mining and especially to identify textual markers of subjectivity and objectivity. The arguments that are made about or against purported facts have a different form from the arguments that are made about opinions. Arguments about objective statements provide the reasons for believing a purported fact or how certain it is. Subjective arguments might indicate, for instance, which users would benefit from a service or product (those similar to the poster). Another area where subjective arguments may appear is discussions of the trust and credibility about the people making the arguments.

Talking is (virtual) work -supporting online argumentation--2013-09-18 Malta virtual work Talking is (virtual) work -supporting online argumentation--2013-09-18 Malta virtual work Presentation Transcript

  • Copyright 2011 Digital Enterprise Research Institute. All rights reserved. Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge Talking is (virtual) work: Supporting online argumentation Jodi Schneider Weds 18th September 2013 1 Dynamics of Virtual Work Training School Valletta, Malta
  • Ph.D. student o Information Management on the Web o Open collaboration systems o Multidisciplinary, mixed methods @jschneider jodischneider.com
  • Open Collaboration Systems o Wikipedia o OpenStreetMap o Project Gutenberg – Distributed Proofreaders o Apache projects, Mozilla Firefox, … In these Open Collaboration Systems “people form ties with others & create things together” (Forte and Lampe 2013)
  • How do we learn the “talk”?
  • Online “talk” for decisions
  • What’s an Open Collaboration System? “An online environment that (1) supports the collective production of an artifact (2) through a technologically mediated collaboration platform (3) that presents a low barrier to entry and exit, and (4) supports the emergence of persistent but malleable social structures.” (Forte and Lampe 2013)
  • What’s an Open Collaboration System? “An online environment that (1) supports the collective production of an artifact (2) through a technologically mediated collaboration platform (3) that presents a low barrier to entry and exit, and (4) supports the emergence of persistent but malleable social structures.” (Forte and Lampe 2013) “Group” collaborating
  • What’s an Open Collaboration System? “An online environment that (1) supports the collective production of an artifact (2) through a technologically mediated collaboration platform (3) that presents a low barrier to entry and exit, and (4) supports the emergence of persistent but malleable social structures.” (Forte and Lampe 2013) How things get done
  • OBSERVATIONS “Group” collaborating Make explicit things get done.
  • Support Newcomers by Making Rules Explicit o Investigate Wikipedia discussions o Provide semantic support o Evaluate the impact on the community
  • Deletion threatens Wikipedia o 1 in 4 new Wikipedia articles is deleted – within minutes or hours o Demotivating! • 1 in 3 newcomers start by writing a new article • 7X less likely to stay if their article is deleted! o Can we support editor retention?
  • Article creators o Misunderstand policy • “I do understand that articles on wikipedia need to be sourced… it is due to have two [sources] once [our website goes] live” o Express high levels of emotion • “To be honest it's been a real turn off adding articles to WP and I don't think I will add articles again. So smile and enjoy.” o Learn from discussions • “much as it would break my heart … it is perhaps sensible that the piece is deleted.” Jodi Schneider, Alexandre Passant, and Stefan Decker. “Deletion Discussions in Wikipedia: Decision Factors and Outcomes.” In WikiSym2012.
  • Novices’ arguments o Structurally different to experts’ arguments o More problematic arguments from novices • Personal preference • Requesting a favor • Analogy to other cases • No harm in keeping an article • Large number of search engine hits Jodi Schneider, Krystian Samp, Alexandre Passant, Stefan Decker. “Arguments about Deletion: How Experience Improves the Acceptability of Arguments in Ad-hoc Online Task Groups”. In CSCW 2013.
  • Articulate criteria 4 Factors cover • 91% of comments • 70% of discussions Factor Example (used to justify `keep') Notability Anyone covered by another encyclopedic reference is considered notable enough for inclusion in Wikipedia. Sources Basic information about this album at a minimum is certainly verifiable, it's a major label release, and a highly notable band. Maintenance …this article is savable but at its current state, needs a lot of improvement. Bias It is by no means spam (it does not promote the products). Other I'm advocating a blanket "hangon" for all articles on newly- drafted players Jodi Schneider, Alexandre Passant, and Stefan Decker. “Deletion Discussions in Wikipedia: Decision Factors and Outcomes.” In WikiSym2012.
  • Add semantic structure Implementation based on Jodi Schneider and Krystian Samp “Alternative Interfaces for Deletion Discussions in Wikipedia: Some Proposals Using Decision Factors. [Demo]” In WikiSym2012.
  • 84% prefer our system “Information is structured and I can quickly get an overview of the key arguments.” “The ability to navigate the comments made it a bit easier to filter my mind set and to come to a conclusion.” “It offers the structure needed to consider each factor separately, thus making the decision easier. Also, the number of comments per factor offers a quick indication of the relevance and the deepness of the decision.”
  • Thanks! o Questions? o Comments? o jschneider@pobox.com o @jschneider
  • Acknowledgements o Thanks to collaborators! • Krystian Samp • Maciej Dabrowski o Overall Ph.D. funding, Science Foundation Ireland Grant No. SFI/08/CE/I1380 (Líon-2), advised by Alexandre Passant, John Breslin & Stefan Decker
  • image credit: Alexandre Passant
  • Goals ! "#$%&' ( )*+, ( - #./0", #1234)5%#$ 61%7 $( 8&( 9: %/ %1 - ( .4%1#$) ; , "1"%14)< ) =#$' ( 4 >1?' ".+ Find and Verify Evidence High Low Low ! "40%@( .+ Find and Defend a Suitable Hypothesis High Low Low >1A%.: #/%1BC( ( D"1& Acquire or Give Information High Low Low ! ( $"E( .#/%1 Coordinate Goals and Actions High Varies High - ( .4' #4"%1 Persuade Other Party Varies High High F ( &%/ #/%1 Get What You Most Want Low Varies High 9."4/ 0 Verbally Hit Out at Opponent Low High High Walton & Krabbe. D. N. Walton. Commitment in dialogue. State University of New York Press, Albany, 1995.