Investigating the Use of Social Software for the Study of Narrative Digital Contexts

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This provides an overview of the project's findings and suggest further research directions.

This provides an overview of the project's findings and suggest further research directions.

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  • 1. Tags, Networks and Narrative Investigating the Use of Social Software for the Study of Narrative Digital Contexts Bruce Mason & Sue Thomas, De Montfort University Presented at De Montfort University 18 September 2007
  • 2. Tags, Networks and Narrative
    • Unlike knowledge repositories, which follow a people-to-documents model, knowledge networks are inherently people-to-people. Bush.A.A. & Tiwana.A., ‘Designing Sticky Knowledge Networks’ Communications of the ACM, May 2005/Vol.48, No.5. p.70
    • Transliteracy: the ability to read, write and interact across a range of platforms, tools and media from signing and orality through handwriting, print, TV, radio and film, to digital social networks. http://www.transliteracy.com
  • 3. Research Questions
    • What kinds of collaborative social network tools are available for the gathering and classification of information?
    • Which researchers are making online narratives the focus of study, and how are those projects categorised by discipline?
    • How can these researchers make effective use of social network tools to share knowledge and develop interdisciplinary collaborations?
  • 4. Aims
    • Evaluate the potential of new tools for the sharing and classifying of knowledge, and identify the accompanying opportunities and threats.
    • Obtain an overview of current research into narratives in a digital context.
    • Disseminate findings
    • Identify topics for further investigation.
  • 5. Objectives
    • Produce a survey of recent collaborative social network tools.
    • Create a database of researchers working with narratives in a digital context and identify a group to test tools used during the project.
    • Set up and evaluate a series of social software tools.
    • Conduct a seminar presenting project findings and initiating discussion.
    • Generate a revised set of research questions to inform further investigation.
  • 6. Coming up
    • Surveying social software tools.
    • Surveying researchers and resources in the area.
    • Trialling online social software.
      • Investigating tagging and folksonomy.
    • Reporting back
  • 7. Folksonomy
    • Folk + taxonomy
    • “ Folksonomy is the result of personal free tagging of information and objects (anything with a URL) for one's own retrival. The tagging is done in a social environment (usually shared and open to others). Folksonomy is created from the act of tagging by the person consuming the information.” ( Vanderwal.net )
    Thomas Vander Wal
  • 8. Del.icio.us
  • 9. Into del.icio.us
  • 10. Del.icio.us compared to FURL
  • 11. Compared to Stumbleupon
  • 12. Stumbleupon social
  • 13. StumbleUpon Inline
  • 14. Ma.gnolia
  • 15. Choosing del.icio.us
    • Simple
    • Well-known
    • Easy to extract data
    • Very restrictive tagging options
    • http:// Del.icio.us in action (hopefully).
  • 16. Exploring tagging
    • Using Del.icio.us
    • 33 taggers started, 28 finished.
    • 40 websites
    • 4 tasks
  • 17. Tagging study
    • Tag 40 sites individually in batches of 10.
    • Break into groups. ( Blog )
    • Inspect other group members’ tags.
    • Derive up to 5 “key” tags for group. Re-tag 5 of the sites as a group.
    • Follow up questions.
  • 18. Roner00
  • 19. Tag clouds
  • 20. Into the Tagverse
    • Project Steve discovered that folksonomy generated roughly 70% more entries than the official taxonomy.
    • We found - 1396 unique tags
    • Wordnet 721 - unique words
    • +94%
    • 1152 “cleaned” tags – (60% more)
  • 21. Tagging issues
    • Is “blog” different from “blogs”?
    • ww2 WW2 wwii worldwar2 World-War-2
    • Is a shortstory a story?
  • 22. Visualizing the tagverse
  • 23. Tagging Patterns
    • Narrow tagging vs broad tagging
      • One person used 224 tags (for just 40 sites).
      • Most had around 100-120
      • Most taggers expressed a preference for:
        • people with a small number of tags;
        • People with descriptive notes.
    • Indexing vs describing
  • 24. Tagging - mixed motivations
    • I picked tags that would be useful for the research I saw myself doing in the future. I did not consider others because my tags are about my research, not theirs. If they would like to use my resource that is fine, but it is primarily for my own use.
    • In the experiment tasks, my primary concern was to choose tags useful to everybody - now my emphasis is on usefulness for my own purposes.
    • Before this experiment it was a line between for me and for others, a mid point.  Now it is all for other people, an entry into multiple points of entry instead of a cloud in one nexus point.   Interesting.  I try to think more of the different areas of interest and context that people may come to it with, more like when I publish an essay on several areas applicable to several fields.  I didn't really do that before.
  • 25.
    • Tagging that is useful for the individual or a particular community will not be useful for the mass and vice versa.  Some people in our group tagged for the mass and so we ended up agreeing on such tags as 'narrative' and 'story' which actually say nothing about a site.  As far as I can see, there is no reason why tagging should be as restrictive as I found it to be.  Even by breaking the rules I felt unable to tag in the way I wanted to.
  • 26. Reading others’ tags
    • I enjoyed more the taggings that are accompanied by a note. Otherwise, I feel that the tag itself doesn’t give me enough information to become interested in their web sites. Also the tags can be very personal, which is great. For example someone has a tag called “Calvino”, but the web site is not about Italo Calvino. The web site makes her think of Calvino, it shows the mental links she has made, which I consider great, and it is an interpretation of the web site. I think this is one of the values of tagging: interpretation and mental links, rather than categorisation because of the sake of categorisation, does it make sense?. Also, I liked when people tag with composed words such as “truestories”, “creationmyth”, because there is a bit more of information to become interested. Also I like to find a short collection of tags. I feel lost when there are too many.
  • 27.
    • … described the sites as a highly subjective critique; as if marking an essay or reporting on the sites in order to share his responses with other reader(s).  I would have preferred an objective - and brief- description of the sites.  I didn’t feel that comments like 'boring and geeky to me', ' fun to browse', ' cool idea', ' probably too arty for my taste' were particularly useful as I don’t know this person and have nor idea of what his tastes are anyway. 
  • 28.
    • I prefer my own style of tagging. Sometimes I think I am not a proper tagger as I still have this obsession to keep the amount of tags at bay. Rather than approaching it spontaneous and letting the database do the rest, I want to somehow keep it under control. The result is a rather reduced amount of tags. The effect though is that the tag cloud stays rather concise which I find helpful.
  • 29. Best Practice?
    • Taggers split though most liked the “user-generated” nature of tagging. E.g.
      • I don't think I like the idea of "best practice" as it takes away from the user generated nature of the enterprise.  I do think having some examples of what people have found works would be good so maybe just not setting it up as "best practice" would suffice for me.
  • 30. So what is folksonomy?
    • User-generated metadata?
    • A shared language?
      • Collabulary (common vocabulary)
    • Context-dependent?
  • 31. Folksonomy for transdisciplinary communication?
    • Requires attention to:
      • Why people tag;
      • The practice of tagging;
      • embedding tagging in the work process.
    • Needs means to deploy the resultant folksonomy.
    • Use as a transliteracy tool.
  • 32. Where next?
    • Lecture by Thomas Vander Wal, Leicester, Sep 18, (this) afternoon.
    • Project website for outputs ( http://www.ioct.dmu.ac.uk/tnn/ )
    • Peer-reviewed articles
    • Transliteracy research ( http:// www.transliteracy.com )
  • 33. For:TheEnd
    • Bruce Mason
    • [email_address]
    • http://www.ioct.dmu.ac.uk/tnn/
    • Sue Thomas
    • [email_address]
    • http://www.transliteracy.com
  • 34. Visualization links
    • Self Organising Model: http://www.hum.dmu.ac.uk/cgi-bin/tnnsomsvg4.cgi
    • Wordnet diagrams: http://www.hum.dmu.ac.uk/cgi-bin/sitetags3.cgi
    • Pivot Graph (works in Opera): http://www.hum.dmu.ac.uk/cgi-bin/graphtnntags.cgi