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Some Thoughts on Tagging
Marti HearstUC Berkeley
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Marti Hearst, UW DUB ‘08
Outline
What are Tags? Organizing Tags for Navigation
Facets and faceted navigation How to (semi)automatically create facet
hierarchies
What’s up with Tag Clouds?
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Marti Hearst, UW DUB ‘08
Social Tagging Metadata assignment without all the bother Spontaneous, easy, and tends towards single
terms Usually used in the context of social media
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Marti Hearst, UW DUB ‘08
The Tagging Opportunity At last! Content-oriented metadata in the
large!
Attempts at metadata standardization always end up with something like the Dublin Core author, date, publisher, … yaaawwwwnnn.
I’ve always thought the action was in the subject metadata, and have focused on how to navigate collections given such data.
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Marti Hearst, UW DUB ‘08
The Tagging Opportunity
Tags are inherently faceted ! It is assumed that multiple labels will be assigned
to each item Rather than placing them into a folder Rather than placing them into a hierarchy
Concepts are assigned from many different content categories
Helps alleviate the metadata wars: Allows for both splitters and lumpers
Is this a bird or a robin Doesn’t matter, you can do both!
Allows for differing organizational views Does NASCAR go under sports or entertainment? Doesn’t matter, you can do both!
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Tagging Problems Tags aren’t organized Thorough coverage isn’t controlled for The haphazard assignments lead to problems with
Synonymy Homonymy
See how this author attempts to compensate:
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Marti Hearst, UW DUB ‘08
Tagging Problems / Opportunities
Some tags are fleeting in meaning or too personal toread todo
Tags are not “professional” (I personally don’t think this matters)
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Marti Hearst, UW DUB ‘08
What about Browsing?
I think tags need some organization Currently most tags are used as a direct index into
items Click on tag, see items assigned to it, end of story
Co-occurring tags are not shown Grouping into small hierarchies is not usually done
del.icio.us now has bundles, but navigation isn’t good IBM’s dogear and RawSugar come the closest
I think the solution is to organize tags into faceted hierarchies and do browsing in the standard way
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Faceted Navigation and Flamenco
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Marti Hearst, UW DUB ‘08
The Problem With Hierarchy Most things can be classified in more than one way. Most organizational systems do not handle this well. Example: Animal Classification
otterpenguin
robinsalmon
wolfcobra
bat
SkinCovering
Locomotion
Diet
robinbat wolf
penguinotter, seal
salmon
robinbat
salmon
wolfcobra
otterpenguin
seal
robinpenguin
salmoncobra
batotterwolf
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Marti Hearst, UW DUB ‘08
Inflexible Force the user to start with a particular category What if I don’t know the animal’s diet, but the
interface makes me start with that category?
Wasteful Have to repeat combinations of categories Makes for extra clicking and extra coding
Difficult to modify To add a new category type, must duplicate it
everywhere or change things everywhere
The Problem with Hierarchy
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Marti Hearst, UW DUB ‘08
The Problem With Hierarchy
start
salmon bat robin wolf
feathersfur scales fur scales feathers fur scales feathers …Covering:
swim fly run slitherLocomotion:
fish
rodents
insects
fish
rodents
insects
fish
rodents
insects
fish
rodents
insects
fish
rodents
insects
fish
rodents
insects
fish
rodents
insects
fish
rodents
insects
fish
rodents
insects
Diet:
otter
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Marti Hearst, UW DUB ‘08
The Idea of Facets
Facets are a way of labeling data A kind of Metadata (data about data) Can be thought of as properties of items
Facets vs. Categories Items are placed INTO a category system Multiple facet labels are ASSIGNED TO items
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Marti Hearst, UW DUB ‘08
The Idea of Facets Create INDEPENDENT categories (facets)
Each facet has labels (sometimes arranged in a hierarchy)
Assign labels from the facets to every item Example: recipe collection
Course
Main Course
CookingMethod
Stir-fry
Cuisine
Thai
Ingredient
Bell Pepper
Curry
Chicken
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The Flamenco Interface
Fine Arts Museum Example
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Advantages of the Approach
Systematically integrates search results: reflect the structure of the info architecture retain the context of previous interactions
Gives users control and flexibility Over order of metadata use Over when to navigate vs. when to search
Allows integration with advanced methods Collaborative filtering, predicting users’
preferences
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Marti Hearst, UW DUB ‘08
Advantages of Facets Can’t end up with empty results sets
(except with keyword search) Helps avoid feelings of being lost. Easier to explore the collection.
Helps users infer what kinds of things are in the collection.
Evokes a feeling of “browsing the shelves” Is preferred over standard search for
collection browsing in usability studies. (Interface must be designed properly)
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Marti Hearst, UW DUB ‘08
Related Work:Automated Tag Organization
Some efforts are on tag prediction: Mishne ’06:
Uses IR techniques to find the closest tagged documents, uses their tags to assign new tags. Measures on how well new tags predicted
Xu et al. ’06: Use tags that have already been predicted for a document to
predict which to show to a new user who is tagging the document Some efforts on tag organization:
Brooks & Montanez ’06: Tries to see if tags can predict document clusters, which in my
book aren’t really categories After clustering based on text they try to induce a tag hierarchy
by agglomerative clustering the text. Results not described in detail
Begelman et al. ’06: Use clustering and tag co-occurrence to find associated tags. Not
clear what the organizational goal is
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How to Create Facet Hierarchies?
Our Approach: Castanet(Stoica & Hearst, to appear at HLT-NAACL ’07)
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Marti Hearst, UW DUB ‘08
Example: Recipes (3500 docs)
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Castanet Output (shown in Flamenco)
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Castanet Output (shown in Flamenco)
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Castanet Output (shown in Flamenco)
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Marti Hearst, UW DUB ‘08
Example: Biology Journal TitlesCastanet Output (shown in Flamenco)
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Marti Hearst, UW DUB ‘08
Castanet Algorithm
Leverage the structure of WordNet
Doc
umen
ts
WordNet
Get hypernym
paths
Sel
ect
ter
ms
Build tree
Compresstree
Divide into facets
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Marti Hearst, UW DUB ‘08
1. Select Terms
red blue
Select well distributed terms from collection
Doc
ume
nts
WordNet
Get hypernym
pathsSel
ect
term
s
Build tree
Comp. tree
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Marti Hearst, UW DUB ‘08
2. Get Hypernym Path
red blue
chromatic color
abstraction
property
visual property
color
red, redness
abstraction
property
visual property
color
blue, blueness
chromatic color
Doc
ume
nts
WordNet
Get hypernym
pathsSel
ect
te
rms
Build tree
Comp. tree
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Marti Hearst, UW DUB ‘08
3. Build Tree
red blue
chromatic color
abstraction
property
visual property
color
red, redness
abstraction
property
visual property
color
blue, blueness
chromatic color
red blue
abstraction
property
visual property
color
red, redness
chromatic color
blue, blueness
Doc
ume
nts
WordNet
Get hypernym
pathsSel
ect
te
rms
Buildtree
Comp. tree
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Marti Hearst, UW DUB ‘08
4. Compress Tree
Doc
ume
nts
WordNet
Get hypernym
pathsSel
ect
te
rms
Build tree
Comp.tree
red, redness
color
red
chromatic color
blue, blueness
blue
green, greenness
green green red
color
chromatic color
blue
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Marti Hearst, UW DUB ‘08
4. Compress Tree (cont.)
red
color
chromatic color
blue green
color
red blue green
Doc
ume
nts
WordNet
Get hypernym
pathsSel
ect
te
rms
Build tree
Comp. tree
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5. Divide into Facets
Divide into facets
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Disambiguation Ambiguity in:
Word senses Paths up the hypernym tree
Sense 1 for word “tuna”organism, being => plant, flora => vascular plant => succulent => cactus
=> tuna
Sense 2 for word “tuna”organism, being => fish => food fish => tuna => bony fish => spiny-finned fish => percoid fish => tuna
2 paths for same word
2 paths for
same sense
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How to Select the Right Senses and Paths?
First: build core tree (1) Create paths for words with only one sense (2) Use Domains
Wordnet has 212 Domains medicine, mathematics, biology, chemistry, linguistics, soccer, etc.
Automatically scan the collection to see which domains apply The user selects which of the suggested domains to use or
may add own Paths for terms that match the selected domains are added to
the core tree
Then: add remaining terms to the core tree.
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Marti Hearst, UW DUB ‘08
Castanet Evaluation Method
Information architects assessed the category systems
For each of 2 systems’ output: Examined and commented on top-level Examined and commented on two sub-levels Also compared to a baseline system
Then comment on overall properties Meaningful? Systematic? Likely to use in your work?
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CastaNet Evaluation Results Results on recipes collection for
“Would you use this system in your work?” # “Yes in some cases” or “yes, definitely”:
Castanet: 29/34 LDA: 0/18 Subsumption: 6/16 Baseline: 25/34
Average response to questions about quality (4 = “strongly agree”)
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Will Castanet Work on Tags? Class project by Simon King and Jeff Towle,
2004 1650 captions captured from mobile phones
“Blocks with Grandpa”, “Weezer” , “A veterans day tour of berkeley in front of south hall.”, “Bad photo”, “Kitchen”, “Jgj ”
Wanted to organize them. Use the CastaNet wordnet-based facet-
hierarchy creation algorithm by Stoica & Hearst, to appear at HLT-NAACL ’07 Had to first remove proper names
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Example Photos & Captions (King & Towle)
very scary x-mas tree Hp presentation
chasing a cat in the dark My cat
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instrumentality, (112) vehicle (26)
car (9) bike (8) vessel, watercraft (4)
mayflower (2) ferry (1) gig (1)
truck (3) airplane (2)
device (20) machine (7)
computer (4) laptop (1) sander (1)
container (16) vessel (7)
bottle (5) water_bottle (2) jug (1) pill_bottle (1)
bath (2) bowl (1)
can (2) backpack (1) bumper (1) empty (1) salt_shaker (1)
furniture, piece of furniture, article of furniture (12)
seat (8) bench (2) chair (2) couch (2) lounge (1)
bed (4) desk (1)
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Research Questions for Tags & Search
The role of interface on tag convergence There seems to be a big effect Would be really interesting to experiment with this Also, for facet grouping
Anchor text vs. tags? How are they the same; how do they differ?
How to get tag expertise? Right now, in many cases it is least-common-
denominator ESP-game
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What’s up with Tag Clouds?
What does a typical tag cloud look like?
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Definition
Tag Cloud: A visual representation of social tags, organized into paragraph-style layout, usually in alphabetical order, where the relative size and weight of the font for each tag corresponds to the relative frequency of its use.
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Definition
Tag Cloud: A visual representation of social
tags, organized into paragraph-style layout, usually in alphabetical order,
where the relative size and weight of the
font for each tag corresponds to the relative frequency of its use.
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flickr’s tag cloud
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del.icio.us
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del.icio.us
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blogs
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ma.gnolia.com
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NYTimes.com: tags from most frequent search terms
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IBM’s manyeyes project
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Amazon.com: Tag clouds on term frequenies
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Alternative: “Semantic” Layout Improving
Tag-Clouds as Visual Information Retrieval Interfaces, Yusef Hassan-Monteroa, 1 and Víctor Herrero-Solana, InSciT2006
Tags grouped by “similarity, based on clustering techniques and co-occurrence analysis”
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I was puzzled by the questions:
What are designers and authors’ intentions in creating or using tag clouds?
How do they expect their readers to use them?
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On the positive side:
Compact Draws the eye towards the most frequent
(important?) tags You get three dimensions simultaneously!
alphabetical order size indicating importance the tags themselves
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Weirdnesses
Initial encounters unencouraging Some reports from industry:
Is the computer broken? Is this a ransom note?
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Marti Hearst, UW DUB ‘08
Weirdnesses Violates principles of perceptual design
Longer words grab more attention than shorter Length of tag is conflated with its size
White space implies meaning when there is none intended Ascenders and descenders can also effect focus
Eye moves around erratically, no flow or guides for visual focus
Proximity does not hold meaning The paragraph-style layout makes it quite arbitrary which terms
are above, below, and otherwise near which other terms
Position within paragraph has saliency effects Visual comparisons difficult (see Tufte)
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Marti Hearst, UW DUB ‘08
Weirdnesses
Meaningful associations are lost Where are the
different country names in this tag clouds?
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Weirdnesses
Which operating systems are mentioned?
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Marti Hearst, UW DUB ‘08
Tag Cloud Study (1)
First part compared tag cloud layouts Independent Variables:
Tag size Tag proximity to a large font Tag quadrant position
Task: recall after a distractor task 13 participants; effects for size and
quadrant Second part compared tag clouds to
lists 11 participants Tested recognition (from a set of like
words) and impression formation Alphabetical lists were best for the
latter; no differences for the former
Getting our head in the clouds: Toward evaluation studies of tagclouds, Walkyria Rivadeneira Daniel M. Gruen Michael J. Muller David R. Millen, CHI 2007 note
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Marti Hearst, UW DUB ‘08
Tag Cloud Study (2)
62 participants did a selection task (find this country out of a list of 10
countries) Independent Variables:
Horizontal list Horizontal list, alphabetical Vertical list Vertical list, alphabetical Spatial tag cloud Spatial tag cloud, alphabetical
Order for non-alphabetical not described
Alphabetical fastest in all cases, lists faster than spatial
May have used poor clouds (some people couldn’t “see” larger font answers)
An Assessment of Tag Presentation Techniques; Martin Halvey, Mark Keane, poster at WWW 2007.
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A Justifying Claim
You get three dimensions simultaneously! alphabetical order size indicating importance the tags themselves
… but is this really a conscious design decision?
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Marti Hearst, UW DUB ‘08
Solution: Celebrity Interviews
I was really confused about tag clouds, so I decided to ask the people behind the puffs 15 interviews, conducted at foocamp’06
Several web 2.0 leaders
5 more interviews at Google and Berkeley
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A Surprise 7 interviewees DID NOT REALIZE that
alphabetical ordering is standard. 2 of these people were in charge of such sites but
had had others write the code
What was the answer given to “what order are tags shown in?” hadn’t thought about it don’t think about tag clouds that way random order ordered by semantic similarity
Suggests that perhaps people are too distracted by the layout to use the alphabetical ordering
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Suggested main purposes: To signal the presence of tags on the site
A good way to get the gist of the site
An inviting and fun way to get people interacting with the site
To show what kinds of information are on the site Some of these said they are good for navigation
Easy to implement
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Tag Clouds as Self-Descriptions
Several noted that a tag cloud showing one’s own tags can be evocative A good summary of what one is thinking and
reading about Useful for self-reflection Useful for showing others one’s thoughts
One example: comparing someone else’s tags to own’s one to see what you have in common, and what special interests differentiate you
Useful for tracking changes in friends’ lives Oh, a new girl’s name has gotten larger; he must have a
new girlfriend!
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Tag Clouds as showing “Trends” Several people used this term, that tag clouds
show trends in someone’s behavior Trends are usually patterns across time, which are
not inherently visible in tag clouds To note a trend using a tag cloud, one must
remember what was there at an earlier time, and what changed tracking the girls’ names example
This suggests a reason for the importance of the large tags – draws one’s attention to what is big now versus was used to be large.
Suggests also why it doesn’t matter that you can’t see small tags.
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Marti Hearst, UW DUB ‘08
New Perspective: Tag Clouds are Social!
It’s not about the “information”! Not surprising in retrospect; tagging is in
large part about the social aspect Seems to work mainly when the tags can be seen
by many Even better when items can be tagged by many
and seen by many
What does this mean though when tag clouds are applied to non-social information?
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Marti Hearst, UW DUB ‘08
Follow-up Study Informed by the interview results, we search for, read,
and coded web pages that mentioned tag clouds. Looked at about 140 discussions Developed 21 codes Looked at another 90 discussions
Used web queries: “tag clouds”, usability tag clouds, etc Sampled every 10th url
58% personal blogs 20% commercial blogs 10% commercial web pages rest from group blogs and discussion lists
Doesn’t tell us what people who don’t write about tag clouds think.
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The Role of Popularity Popularity in the sense that tag clouds (and tagging)
are trendy and popular. Some people liked the visualization, but their popularity
made them less appealing Famous post: “Tag clouds are the new mullets” Led to self-consciousness about liking them
Many complained about unaesthetic cloud designs Little consensus on if they are a fad or have staying power
Popularity also in the sense of the large font size for more popular tags Many people like the prominence of large tags, but several
commented on the tyranny of the popular
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The Role of Navigation
Opinions vary Many simply state they are useful for navigation,
but with no support for this claim Some claim the compactness makes navigation
easier than a vertical list Some object to the varying font size on
scannability Others object to the lack of organization Overall, there is no evidence either way that we
could find in the blog community
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Marti Hearst, UW DUB ‘08
Aesthetic Considerations
Disagreement on the aesthetic and emotional appeal, especially for lay users.
Those who like them find them fun and appealing
Those who don’t find them messy, strange, like a ransom note
Informal reports with first time users who are not in the Web 2.0 community are negative
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Trends again
As in the interviews, the benefit of “trends” was mentioned many times.
There is another sense of “trend” as “tendency or inclination,” and this might be what people mean.
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Marti Hearst, UW DUB ‘08
Summary of Stated Reasons for Tag Clouds
(Note: some refuted by studies)
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Tag Clouds as Social Information An emphasis that tag clouds are meant to show
human behavior. We found reports of people commenting on
other uses that were invalid because they did not reflect live user input: One blogger noted the incongruity of an online library
using keyword frequencies in a tag cloud rather than having it reflect patron’s usage of the collection.
An online community noticed one site’s cloud didn’t change over time and realized the sizes were decided by marketing. This was greated with derision.
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Marti Hearst, UW DUB ‘08
Implications
Assume tag clouds are meant to reflect human mental activity (individual or group)
Then what might seem design flaws from an information conveyance perspective may not be
A large part of the appeal is the fun and liveliness. The informality of the layout reflects the human
activity beneath it.
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Judith Donath, CACM 45(4), 2002
“Traditional data visualization focuses on making abstract numbers and relationships into concrete, spatialized images; the goal is to highlight important patterns while also representing the data accurately. This is a fine approach for social scientists studying the dynamics of online interactions. Yet for our purpose it is also important that the visualization evoke an appropriate intuitive response representing the feel of the conversation as well as depicting its dynamics”
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Judith Donath, CACM 45(4), 2002
“[O]ne argument for deliberately designing evocative visualizations for online social environments is the existing default textual interfaces are themselves evocative, they simply evoke an aura of business-like monotony rather than the lively social scene that actually exists.''
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Tag Cloud AlternativesProvided by Martin Wattenberg
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Conclusions
Social tagging is, in my view, a terrific way to get good content metadata.
I think automated techniques can do a lot to help clean them up and organize them.
They are an inherently social phenomenon, part of social media, which is a really exciting area.
The socialness of social media can yield surprises, like tag clouds.