1. data visualization:
clouding
anne helmond & sabine niederer
doing digital methods, rmes workshop, 28 june 2011
2. data visualization
the science of visual representation of “data”,
defined as information which has been abstracted
in some schematic form, including attributes or
variables for the units of information. (2009:1)
michael friendly
17. tag cloud de nition
A tag cloud (word cloud, or weighted list in visual
design) is a visual representation for text data,
typically used to depict keyword metadata (tags)
on websites, or to visualize free form text.
wikipedia
18. tag
In online computer systems terminology, a tag is a
non-hierarchical keyword or term assigned to a
piece of information (such as an internet
bookmark, digital image, or computer le). This
kind of metadata helps describe an item and
allows it to be found again by browsing or
searching. Tags are chosen informally and
personally by the item's creator or by its viewer,
depending on the system.
wikipedia
19. tagging
Tagging systems enable users to add keywords
(i.e., “tags”) to Internet resources (e.g., web pages,
images, videos) without relying on a controlled
vocabulary.
[...] a freely chosen set of keywords (“tags”).
marlow et al 2006
20. folksonomy
A folksonomy is a system of classi cation derived from
the practice and method of collaboratively creating
and managing tags to annotate and categorize
content; this practice is also known as collaborative
tagging, social classi cation, social indexing, and social
tagging. (Wikipedia)
Folksonomy is the result of personal free tagging of
information and objects (anything with a URL) for
one's own retrieval. 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. (Vander Wal 2007)
32. extracting value from big data
The strategy of tagging -- free-form labeling,
without regard to categorical constraints -- seems
like a recipe for disaster, but as the Web has shown
us, you can extract a surprising amount of value
from big messy data sets.
shirky 2005
34. tag exercise 1
Compare privacy policies: Twitter and Facebook
1. Look up privacy policies
2. Copy/paste all text into Wordle
3. Adjust visualizations in Wordle for readability
4. Compare visualizations
35. tag exercise 1
advanced
Compare privacy policies: Twitter and Facebook
1. Look up privacy policies
2. Copy/paste all text into Tagxedo
3. Adjust visualizations in Tagxedo for readability
4. Exclude terms (which ones?)
5. Compare visualizations
37. tag exercise 2
Clouding a current event: Glastonbury
1. Scrape top 1000 tweets for #Glastonbury using
the Twitterscraper
2. Open le in Excel/OpenOffice
3. Copy/paste text column in Tagxedo
4. Exclude terms (which ones?)
5. Compare visualizations
38. tag exercise 2
advanced
Clouding a current event: Glastonbury on Twitter
and in Google News
1. Use previous instructions for Twitter
2. Enter keyword Glastonbury in Tagxedo
3. Adjust visualizations in Tagxedo for readability
4. Exclude same terms as Twitter
5. Compare visualizations