Social Networks in Intercultural Collaboration Ari Hautasaari 25.11.2008

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

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

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

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

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

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

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

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

Collaborative Translation and Social Networks

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?

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

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

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)

Research Methods

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)

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)

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

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

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)

Discussion