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INTRODUCING CULTURAL PROMPTS IN A SEMANTIC DATA BROWSER Dhaval Thakker , Vania Dimitrova, Gaye Ediboğlu International Workshop on Intelligent Exploration of mantic Data (IESD) 2012
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Introducing cultural prompts in a semantic data browser

Oct 18, 2014

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Page 1: Introducing cultural prompts in a semantic data browser

INTRODUCING CULTURAL PROMPTS IN A SEMANTIC DATA BROWSER

Dhaval Thakker, Vania Dimitrova, Gaye Ediboğlu

International Workshop on Intelligent Exploration of Semantic Data (IESD) 2012

Page 2: Introducing cultural prompts in a semantic data browser

Exploitation of digital traces as a source for informal learning

Page 3: Introducing cultural prompts in a semantic data browser

digimind.com

digital traces

Exploration Environment

Taming•Retrieve•Aggregate•Organise

Semantic Web Technologies• Semantic Data browsers• Semantic Nudges

Exploitation of digital traces as a source for informal learning

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Semantic Data BrowserFocus Concept

Facts

Social Content

Eye Contact is Body Language

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Semantic Data Browser

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Processing Pipeline: Semantic Data Browser

Digital Traces Collection

Ontology Underpinning

Semantic Augmentation &

Query

Browsing & Interaction

Bespoke Ontologies & Linked Data Cloud

Page 7: Introducing cultural prompts in a semantic data browser

• Data browsers Limitations:• Cognitive onus on Learner• Not always possible to decide best course of action

for him/her.

Semantic Data Browser for Learning

•Influence options in a way that will support choosers to act in their own interest, preserving freedom of choice•Signposting & Prompts

Thakker, D., Dimoklis, D.,Dimitrova, V., Lau, L., Brna, P. (2012) Taming Digital Traces for Informal Learning: A Semantic-Driven Approach. EC-TEL 2012, pp. 348--362. Springer, Heidelberg,  Saarbrücken (Germany), 18 - 21 September 2012. 

Page 8: Introducing cultural prompts in a semantic data browser

Semantic Nudges: Signposting

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Semantic Nudges: Prompts

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Semantic Data Browser

Interaction FocusUser: Country of origin, visited,

residence

Digital Traces Ontology

Digital Traces + Semantic Tags

So far…Semantic Data Browser

Page 11: Introducing cultural prompts in a semantic data browser

• Hofstede: “[culture is] the collective programming of the human mind that distinguishes the members of one human group from those of another. Culture in this sense is a system of collectively held values.” [12].

• National culture is fundamental for distinguishing the people of one country from other people from other countries.

• Intercultural communication – cultural differences in terms of personal distance, gestures, body language, norms

http://geert-hofstede.com/geert-hofstede.html

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Culture awareness & Exposure

• Cultural awareness is “.. understanding some key facts about a particular culture”.

• Cultural exposure is experience of culture by visit/origin/residence.

• Aim: Inform users about cultural aspects (basics, intercultural dimensions – such as gestures)

Page 13: Introducing cultural prompts in a semantic data browser

Cultural Models for National Cultures: Hofstede Model

http://geert-hofstede.com/national-culture.html

Page 14: Introducing cultural prompts in a semantic data browser

Power Distance(The degree to which power differentials within society and

organizations are accepted.)

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United Kingdom & China

IDV

In Individualist societies people are supposed to look after themselves and their direct family only.

In Collectivist societies people belong to ‘in groups’ that take care of them in exchange for loyalty.

LTO

The extent to which a society shows a pragmatic future-oriented perspective rather than a conventional historical short-term point of view.

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Stereotypical Information from Hofstede model - for UK

• Power distance• At 35 Britain sits in the lower rankings of PDI – i.e. a society that believes that

inequalities amongst people should be minimized.• Individualism

• At a score of 89 the UK is amongst the highest of the individualistic scores, beaten only by some of the commonwealth countries it spawned i.e. Australia and the USA.

• Masculinity / Femininity• At 66 Britain is a masculine society – highly success oriented and driven. A key point of

confusion for the foreigner lies in the apparent contradiction between the British culture of modesty and understatement which is at odds with the underlying success driven value system in the culture.

• Uncertainty avoidance • At 35 the UK has a low score on uncertainty avoidance which means that as a nation

they are quite happy to wake up not knowing what the day brings and they are happy to ‘make it up as they go along’ changing plans as new information comes to light.

• Long term orientation• At 25 the UK scores as a short term oriented society which drives a great respect for

history and tradition as well as a focus on quick results in the future.

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Grouping countries in clusters for measuring exposure to more abstract

level• Hofstede Model: K-mean Clustering

Cluster 1Netherlands,

Norway, Sweden, Denmark, Finland

Available from : http://imash.leeds.ac.uk/publications/support/culturalprompts/

Cluster 2El Salvador, Turkey,

Chile, Portugal, Uruguay, Greece,

Spain

Cluster 3China, Indonesia, Ghana, Nigeria, Singapore, Hong

Kong, Kenya

Cluster 4Malaysia,

Philippines, India

Cluster 5Panama, Mexico,

Venezuela, Ecuador, Colombia

Cluster 6Egypt, Iraq, Kuwait,

Lebanon, Libya, UAE, Saudi Arabia,

Brazil, Iran

Cluster 7France, Poland, Belgium, Czech

Republic, Japan, Italy, Argentina, Hungary

Cluster 8USA, Australia, UK,

Ireland, New Zealand

Cluster 9South Africa,

Germany, Switzerland, Austria

Cluster 10Peru, Thailand,

Pakistan, Taiwan, South Korea

Page 18: Introducing cultural prompts in a semantic data browser

National Culture Models: Globe project

• Cross-cultural research effort – wider in scope, depth, duration. • Nine units of measurement – cultural dimensions

Performance Orientation

Uncertainty Avoidance

Humane Orientation

Institutional Collectivism

In-Group Collectivism Assertiveness

Gender Egalitarianism

Future Orientation Power Distance

http://www.grovewell.com/pub-GLOBE-intro.html

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Globe Cultural Model: Clusters

Anglo - 7 Latin Europe - 6Nordic Europe - 3 Germanic Europe - 5Eastern Europe - 8 Latin America - 10Sub-Saharan Africa - 5 Middle East - 5Southern Asia - 6 Confucian Asia - 6

Page 20: Introducing cultural prompts in a semantic data browser

…Semantic Data Browser + Cultural Model

Semantic Data Browser

Interaction FocusUser: Country of origin, visited,

residence

Digital Traces Ontology

Cultural Models

Culture dimensions Stereotypical Information

Culture clusters

Digital Traces + Semantic Tags

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User Model : Culture exposure of user mapped to Cultural Models

• U = < Corigin, Cresidence, Cvisited, Ehof, Eglobe>

• Ehof & Eglobe = Mapping Corigin, Cresidence, Cvisited to Hofstede Clusters and Globe Clusters

• For example, a user who has visited Egypt, Iraq, Kuwait, Lebanon, Libya, India

Cluster 1Netherlands,

Norway, Sweden, Denmark, Finland

Cluster 2El Salvador, Turkey,

Chile, Portugal, Uruguay, Greece,

Spain

Cluster 3China, Indonesia, Ghana, Nigeria, Singapore, Hong

Kong, Kenya

Cluster 4Malaysia,

Philippines, India

Cluster 5Panama, Mexico,

Venezuela, Ecuador, Colombia

Cluster 6Egypt, Iraq, Kuwait,

Lebanon, Libya, UAE, Saudi Arabia,

Brazil, Iran

Cluster 7France, Poland, Belgium, Czech

Republic, Japan, Italy, Argentina, Hungary

Cluster 8USA, Australia, UK,

Ireland, New Zealand

Cluster 9South Africa,

Germany, Switzerland, Austria

Cluster 10Peru, Thailand,

Pakistan, Taiwan, South Korea

56%

33%

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…Semantic Data Browser + Cultural Model + User Model

Semantic Data Browser

Interaction FocusUser: Country of origin, visited,

residence

Digital Traces Ontology

Cultural Models

Culture dimensions Stereotypical Information

Culture clusters

User Model

User Model

Digital Traces + Semantic Tags

Page 23: Introducing cultural prompts in a semantic data browser

…Semantic Data Browser + Cultural Model + User Model = Prompt Model

Semantic Data Browser

Interaction FocusUser: Country of origin, visited,

residence

Digital Traces Ontology

Cultural Models

Culture dimensions Stereotypical Information

Culture clusters

User Model

User Model

Digital Traces + Semantic Tags

Prompt Model

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Goals of Prompts

• G1. Create awareness of cultural aspects. In the cases when the evidence (from user model) suggests that no exposure to a particular cultural cluster exist, i.e. Ehof<ClusterHofi, Val) Val = ϕ ∧ ∨Eglobe<ClusterGloi, Val) Val = ϕ∧ .

• G2. Expand awareness on certain cultural aspects. In the cases when the evidence (from user model) suggests that there is a limited exposure to a particular culture cluster, where the limit is some threshold θ

• G3. Reflect on cultural awareness. In the cases when the evidence (from user model) suggests that there is good exposure to a particular culture cluster

Page 25: Introducing cultural prompts in a semantic data browser

Prompt Model: Using User Model, Globe Model

• User Model: No exposure to Globe cultural cluster (‘Eastern Europe’)

• General Goal: Create Awareness • Aim: to create awareness for the ‘Eastern

Europe’ cluster and influence the content user browses.

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Prompt Model: Using User Model, Globe Model

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Prompt Model: Using User Model, Hofstede Model

• User Model: The user has exposure to countries with contrasting power distance index (PDI- as defined by Hofstede)

• General Goal: Create Awareness • Aim: to create awareness by informing about contrasting PDI

Page 28: Introducing cultural prompts in a semantic data browser

Prompt Model: Using User Model, Hofstede Model

• User Model: The user has exposure to countries with contrasting power distance index (PDI- as defined by Hofstede)

• General Goal: Create Awareness • Aim: to create awareness by informing about contrasting PDI

Page 29: Introducing cultural prompts in a semantic data browser

Prompt Model: Using Interaction Focus, Hofstede/Globe Model

• Interaction Focus: The user is at an Entity page, that contains comment mentioning countries.

• Condition: countries mentioned in comment are within a cluster

• Specific Goal: Inform the user about countries belonging to a specific cluster

Page 30: Introducing cultural prompts in a semantic data browser

Future work

• Prompt Model– Type of the prompts and list so far is what can be

generated– Which prompt to display & when (e.g. more than

one matching specific goal) is not worked out yet– “WHAT, HOW” is answered but not “WHEN”– Interaction history can be important– Evaluation

Page 31: Introducing cultural prompts in a semantic data browser

1. Learning context: – Informal Learning is important– Social spaces and user generated content offer new

opportunities

2. Technology:– Semantic Nudges to empower exploration in Semantic

Data Browser– Cultural Prompts for introducing cultural aspects in

semantic data browser

Thank You!Dr Dhaval Thakker, Research Fellow, University of Leeds

[email protected]://www.imreal-project.eu/