1. Social Networks in Intercultural Collaboration
Ari Hautasaari

2. Outline Social networks on the Web
Research plan - Collaborative translation analysis

3. Social Networks on the Web
Previous research on:
SNS (Social Network Services ie. Facebook)
Semantic Web (FOAF)
Web of trust
Ontology construction
Conflict of interest
Information exchange

4. Social Networks on the Web
Previous research topics
Structural properties (groups, subgroups, key individuals, closeness, betweenness, centrality)
Citation (co-citation, semantic structure, citation patterns)
Link-structure analysis
Graph-theory

5. Social Networks on the Web – Problems With the Research
Accuracy of the results suffers from the nature of FOAF and SNS
Information is user input / biased
Networks are often very centralized (lack of data) or unproportioned (difference in amount of data between people)
Time is not concidered as a variable (no ”link-rot” nor dynamic networks)
Number of input and output connections are scarce
Variables in relationships are scarce

6. Document instance usage in FOAF (Finin et. al. 2005)

7. Starshaped networks of FOAF (Finin et. al. 2005)

8. Social Network by Cocitation (Miki, Nomura, Ishida 2005)

9. Social Network Analysis Variables
Betweenness
Closeness
(Degree) centrality
Flow betweenness centrality
Eigenvector centrality
Centralization
Clustering coefficient
Cohesion
(Individual-level) density
Path Length
Radiality
Reach
Structural cohesion
Structural equivalent
Structural hole

10. Collaborative Translation and Social Networks

11. Research Questions
How does social network affect collaborative translation?
Do different social networks have different outcomes on collaborative translation?
How is common ground established?
What problems/phenomena can we find in computer-mediated collaborative translation within organizations?

12. Hypothesis
Social network variables have an effect on the outcome of collaborative translation
Different network
Position in a network
Organizational context
Trust
Common ground is established within a social network

13. Collaborative Translation – Research Progression
Perform analysis on the subject data (Pangaea)
Extract common factors
Build a (statistical) model
Find a (social networking) theory for the model

14. Social Network Dependent Collaborative Translation
Conduct a test using the results of a collaborative translation service
Use members of different social networks as control groups
Outsiders vs. Insiders
Same network, high authority (amount of links)
Same network, low authority
Different network (no, or long path)

15. Research Methods

16. Collaborative Translation – Content Analysis
Quantative content analysis on collaborative translation data
Cultural aspects and change
Communication content in regard to standards
Patterns of communication
Flow of information
(Readability) Level of understanding
(Holsti 1969)

17. Collaborative Translation – Conversation Analysis
Organizational communication
Repair of sentences or utterances
Self-correction vs. Other-correction
How does the organizational context affect the sentence correction in collaborative translation?
(Schegloff, Jefferson, & Sacks 1977)
(Haakana, Kurhila 2006)

18. Collaborative Translation – Context Analysis
Organization analysis
Define the organizational environment
Define the organizational culture
Define the organization structure
Organizational network analysis
Information flow
Social connections

19. Social Network Dependent Collaborative Translation
Analyze the translation results in regard of social network
How do CMC-tools effect the result in different test settings
Level of acceptance with bad translations
Ect…
Analyze common ground
Analyze the effect of social network position on the collaboration
Authority
Path length

20. What next? Clarify hypothesis Clarify research question
Obtain subject data (Pangaea)
Extend literature review on the subject (models & theory)
Work on translation accuracy awareness problem (a problem proposed in Yamashita-san’s paper)

21. Discussion