towards understanding the motivation behind tagging

TU Graz – Knowledge Management Institute

Christian Körner Graz, February 4th, 20111

Towards Understanding the Motivation Behind Tagging

Christian Körner

Knowledge Management InstituteGraz University of Technology

presentation

@Mendeley

PhDWorkInPr

ogress

4Feb2010

taggingmotivation

todoimportant

Friday, February 11, 2011



Outline of Todays Talk

• Introduction• Motivation• Research Questions• Related Work• What happened so far?• Two Different Types of Tagging Motivation• Expected Contribution• Outlook

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Introduction / 1

•Tagging is an easy and intuitive way to annotate resources

•A lot of current web platforms enable the tagging of resources

•Tags:– are simple strings– add additional metadata to a resource– support re-finding of resources– enable the browsing of a user’s resource collection– mostly do not follow a controlled vocabulary

How and which tags are applied to a resource depends on the user!

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Introduction / 2

Examples of Social Tagging Systems

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Introduction / 3

Resulting structure of social tagging systems consists of:– Users– Tags– Resources

Folksonomy (all users of a system)Personomy (one user of a system)

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Motivation

Getting a closer look at the motivation users of tagging systems have

Inferring which users/tags are good for certain tasks:– searching in these systems– ontology learning– classification

Improve tag recommendation engines

Simulation of users and folksonomies

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Research Questions

Is it possible to measure tagging motivation automatically?

How do different motivations influence and transform resulting folksonomies?

Based on these findings: – Can we improve existing mechanisms (such as tag

recommendation)?– Is it possible to simulate whole folksonomies?

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Related Work (excerpt)[Golder2006] - studies folksonomies as a whole, shows stable

patterns. Present a dynamic model of collaborative tagging.

[Nov2009] - different motivations in an online photo sharing system: enjoyment, commitment, self development, reputation

[Heckner2009] - studied resource sharing vs. personal information management in social tagging systems and propose model of information behavior in social tagging systems

But all previous work relies on expert judgement!

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What happened so far?

Identification of two types of tagging motivation (two others are in the pipeline as well)

Developed measures to detect the behavior

Showed how tagging motivation can influence the resulting tags of a folksonomy and ontology learning[Körner2010a]

Evaluated measures to identify the best for the differentiation [Körner2010b]

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Two Different Extreme Types of Tagging Motivation (so far)

Categorizers

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Describers




Categorizers - Using Tags for Categorization

• Main focus: using tags for mimicking a taxonomy created by their personal preferences

• they utilize tags so that their resources can be browsed more easily later

• avoid synonyms• use limited tagging vocabulary• use “subjective” tags

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Describers - Using Tags to Describe Resources

• Main focus: describing resources as detailed as possible

• support search with their usage of tags• tagging vocabulary can contain synonyms• have an open tagging vocabulary• use “objective” vocabulary

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(Current) Detection Measures

Agnostic to semantics of used language

Evaluate user behavior of single user (as opposed to the complete folksonomy)– no comparison to complete folksonomy necessary

Inspect the usage of tags NOT their semantics:– How often are tags used?– How good does a user “encode” her resources with tags?– How many tags are used to annotate a single resource– etc.

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Results

• An early stage of this work was presented at the ACM SRC Hypertext 2009 conference and won the 1st prize

• Cooperation with KDE Kassel which resulted in a publication at the WWW2010

• One of the results of this work is that tagging pragmatics has impact on the semantic structure within a folksonomy

• In essence: “Describers are better for the semantics within a tagging system”

• Evaluation which measures perform best to differ types• Hypertext 2010

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Some additional papersExamining which measures are better for measuring the

generality of tags– Evaluate different folksonomy based measures with the help four different

grounding sets

• Currently under review at ESWC

Identifying the impact of user behavior on automated classification

– Automatically categorizing books into LCC and Dewey Classification Scheme– Categorizers are also good for something!– Although they use not that many words which are found in the descriptive

data, they perform better with regard to classification.

• Currently under review at HT2011

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Expected Contribution

Getting a closer look at the reasons why users tag

Improve recommendation engines

Enhancing search

Enhancement of automated ontology learning

Possible identification of spammers

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Possible Outlook

Examine how tag recommendation can profit from knowledge of user motivation

Investigate additional types of tagging motivation

Using social network analysis for further investigation

Using identified types of tagging motivation to build simulators

Start writing the thesis

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Conclusion

• Insight into my research on motivation behind tagging

• Quick introduction about tagging• Motivation & Research Questions• Related Work

• Categorizer VS. Describers• Work which was done so far• Expected Contribution & Outlook

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Thank You For Your Attention

Please feel free to ask questions!

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References[Ames2007] Ames, M. & Naaman, M. (2007), Why we tag: motivations for annotation in mobile

and online media, in ‘CHI ’07’: Proceedings of the SIGCHI conference on Human factors in computing systems’ ACM, New York, NY, USA, pp.971--980

[Golder2006] Golder S. & Huberman B.; Usage Patterns of Collaborative Tagging Systems; Journal of Information Science; 32(2):198, 2006

[Heckner2009] Heckner, M; Heilemann, M. & Wolff, C. (2009) Personal Information Management vs. Resource Sharing: Towards a Model of Information Behavior in Social Tagging Systems, in ‘Int’l AAAI Conference on Weblogs and Social Media (ICWSM)’.

[Körner2010a] Körner, C.; Benz, D.; Strohmaier, M.; Hotho, A. & Stumme, G. (2010), Stop Thinking, start Tagging - Tag Semantics emerge from Collaborative Verbosity, in 'Proceedings of the 19th International World Wide Web Conference (WWW 2010)', ACM, Raleigh, NC, USA.

[Körner2010b] Körner, C.; Kern, R.; Grahsl, H. P. & Strohmaier, M. (2010), Of Categorizers and Describers: An Evaluation of Quantitative Measures for Tagging Motivation, in '21st ACM SIGWEB Conference on Hypertext and Hypermedia (HT 2010)', ACM, Toronto, Canada.

[Nov2009] Nov, O.; Naaman, M. & Ye, C. (2010), 'Analysis of participation in an online photo-sharing community: A multidimensional perspective.', JASIST 61(3), 555-566.

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