Presentation of the paper "A Framework to Investigate the Relationship Between Employee Embeddedness in Enterprise Social Networks and Knowledge Transfer" by Janine Viol and Caroline Durst in "Witold Pedrycz, Shyi-Ming Chen (Eds). Social Networks: A Framework of Computational Intelligence.
Studies in Computational Intelligence Band 526. Berlin: Springer. 2014." in course "Semantic Modelling" at HTW Berlin, major "Internationale Medieninformatik".
Este documento proporciona recomendaciones de profesores para las materias de Bienes y Derechos Reales, Delitos en Particular y Derecho Constitucional en la Facultad de Derecho. Incluye el nombre del profesor, horario de clases, método de evaluación y comentarios sobre cada profesor. Los comentarios brindan información sobre la calidad de la enseñanza, la dificultad de la evaluación y la cantidad de material aprendido para cada profesor.
Overview of the ploneintranet project and what we've achieved in the past year. Shows how technology can support organisational culture change and smart collaboration.
Data Scopes - Towards transparent data research in digital humanities (Digita...Marijn Koolen
Data scopes describe the process of data gathering, cleaning and combining in digital humanities research, which is too often considered as mere preparation that is not part of research, and is mostly not described in scholarly communications. We argue that scholars need to be more aware of the intellectual effort of this process and make it more transparent
USAID Knowledge Management Building Blocksgvaughan
This document summarizes a World Bank knowledge sharing event on building blocks and stumbling blocks for knowledge management. The event included panel presentations on various frameworks related to KM, including culture, change management, governance, and measurement. It then outlined small group discussion tasks for participants to discuss the implications of these frameworks based on their experiences. The overall goal was to share perspectives on KM and develop recommendations to improve how knowledge is managed and shared within organizations and across networks.
Informal Network - Innovative Internet Second Project MichalGromek
Well developed informal networks can be a significant competitive advantage, both for firms and regions. How likely are engineers to ask their peer for help? What are informal networks?
Este documento proporciona recomendaciones de profesores para las materias de Bienes y Derechos Reales, Delitos en Particular y Derecho Constitucional en la Facultad de Derecho. Incluye el nombre del profesor, horario de clases, método de evaluación y comentarios sobre cada profesor. Los comentarios brindan información sobre la calidad de la enseñanza, la dificultad de la evaluación y la cantidad de material aprendido para cada profesor.
Overview of the ploneintranet project and what we've achieved in the past year. Shows how technology can support organisational culture change and smart collaboration.
Data Scopes - Towards transparent data research in digital humanities (Digita...Marijn Koolen
Data scopes describe the process of data gathering, cleaning and combining in digital humanities research, which is too often considered as mere preparation that is not part of research, and is mostly not described in scholarly communications. We argue that scholars need to be more aware of the intellectual effort of this process and make it more transparent
USAID Knowledge Management Building Blocksgvaughan
This document summarizes a World Bank knowledge sharing event on building blocks and stumbling blocks for knowledge management. The event included panel presentations on various frameworks related to KM, including culture, change management, governance, and measurement. It then outlined small group discussion tasks for participants to discuss the implications of these frameworks based on their experiences. The overall goal was to share perspectives on KM and develop recommendations to improve how knowledge is managed and shared within organizations and across networks.
Informal Network - Innovative Internet Second Project MichalGromek
Well developed informal networks can be a significant competitive advantage, both for firms and regions. How likely are engineers to ask their peer for help? What are informal networks?
How to Scale Information Dissemination to the Virtual Digital WorkspaceXeniT Solutions nv
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The document outlines an agenda for a workshop on social innovation and enterprise at the 2015 Eastern Region AUTM meeting in Raleigh, NC. The workshop will include a panel discussion of experiences with social innovations from UNC Greensboro, University of New Hampshire, and North Carolina State University. Attendees will then break into groups to discuss case studies and paths to commercialization for social innovations. The goals are to analyze commercialization approaches for social innovations and develop best practices to sustain commercialization of non-traditional intellectual property for social benefit.
Protected Area Network Knowledge Management Framework (Needs Assessment and A...John Mauremootoo
PowerPoint presentation given at a consultative workshop to ascertain the knowledge management baseline among protected area stakeholders in Mauritius as a contribution to the development of a Protected Area Knowledge Management System.
This document provides an overview of key concepts relating to data and information strategies. It discusses different data types like categorical, ordinal, ratio and interval data. It also covers data structures, including structured and unstructured data. Big data and the increasing amount of data created is mentioned. The document explores how data can be analyzed and interpreted to inform strategic decisions and actions. It aims to help students understand and apply these concepts in the context of their own work.
Driving Change to Thrive in a Digital FutureNeil Calvert
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The document provides an overview of an event on emerging trends in data science given by Dr. Joanne Luciano. It discusses the data science workflow and various processes involved. Some key trends highlighted include increased use of AI and machine learning in data management and reporting, growth of natural language processing, advances in deep learning, emphasis on data privacy and ethics. The document also promotes the new minor in data science offered at University of the Virgin Islands, covering required courses and examples of course sequences for different disciplines.
The document discusses information systems and digital transformation. It covers topics like structured vs unstructured data, how businesses can leverage data and technology, and challenges around measuring success and the impact of digital initiatives. Examples are provided of how technology is changing work and forcing businesses to adapt. The document also outlines potential deliverables for a course, including a curation page, case study, and video presentation.
How to move Beyond-GDP? An action plannefwellbeing
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Understanding the value of research data analysis for organisations is essential in the age of data-driven decision-making. This extensive guide digs into the area of decoding research data analysis and provides readers with key skills to elucidate insightful business information. Learn how to gather, arrange, and analyse data from various sources to spot trends, correlations, and patterns. Learn how to transform raw data into useful insight by utilising statistical analysis and data visualisation tools. This tool equips professionals with the tools they need to harness the potential of research data analysis and acquire a competitive edge in the quickly changing business environment of today. Its focus is on promoting informed decision-making.
Knowledge management simple secret of sucessfulSeta Wicaksana
Seta A. Wicaksana is a psychologist who works at Humanika Consulting. She has several roles including being a senior advisor at BPJS Ketenagakerjaan and deputy dean at the Faculty of Psychology at Pancasila University. She founded Humanika Consulting and writes books. She develops psychological assessment tools and trains, counsels, and assesses clients. She also teaches at Pancasila University and is pursuing her doctorate there in human resource management.
This document summarizes discussions from a conference on developing science, technology and innovation indicators and policies. Key topics discussed include:
- The need for a systems approach and measuring innovation in all sectors to better inform policy.
- Collecting new data on topics like scientist mobility, refugee migration backgrounds, and knowledge flows to answer important questions.
- Involving stakeholders like scientists, engineers and citizens to understand impacts through participatory processes.
- The limits of indicators and risks of oversimplification or perverse effects from misuse of metrics like rankings.
- Making indicators more inclusive by capturing contributions from new performers and geographical or cognitive areas not traditionally included.
- Opportunities and challenges of
A webinar by Fabrizio Pellizzetti, a Master Black Belt in Lean Six Sigma. In the first half Fabrizio thoroughly discusses what Lean Six Sigma is and the evolution of the methodology. In the second half, he dispels some myths surrounding LSS & clarifies real challenges before ending with the Lean Six Sigma Applicability.
Based on the ‘job track’ methodology developed at Lancaster University, the toolkit comes packed with resources to enable you to develop streamlined job families suitable to your IT organisation. The toolkit will enable you to produce clear information for individual staff to develop their IT careers, and to be supported along the way by their line managers. The toolkit includes a database of job descriptions, case studies and all the resources required to produce innovative and highly visual ‘job tracks’ in the style of an underground map. The pragmatic approach is simpler than a full SFIA implementation and is compatible with competency frameworks used in HE including HERA.
MVO in de tertiaire sector, door Freddy Noris, Sustainable Development Manage...Agoria
This document summarizes a presentation on CSR (corporate social responsibility) at SWIFT. It discusses how SWIFT's CSR program began in 2008 with a focus on environmental initiatives, employee engagement, and acting as a CSR facilitator for the financial industry. It outlines SWIFT's current CSR strategy and how this will impact expectations for its maintenance service suppliers, requiring them to meet ethical and environmental standards. The presentation concludes that CSR must be fully endorsed, embedded in a company's strategy and DNA, and sees it as a source of innovation, competitive advantage, and continuous improvement.
Brief description of ONA (Organizational network analysis) followed by a summary and comparison of the emerging SAAS vendors who provide support for network surveys and analysis.
This document discusses public-private partnerships (P3s) for infrastructure delivery, specifically for transportation projects. It analyzed 8 case studies of past and current P3 transportation projects using qualitative comparative analysis and stakeholder network theory. The analysis aimed to better understand outcomes of P3s and how to manage perceptions of stakeholders. Initial results pointed to need for further methodological refinement to identify clear relationships between factors and outcomes of successful P3 development and delivery. Defining specific measures of success is still being determined but may include meeting schedules for requests for proposals, financial close, construction milestones, and traffic volumes.
ROUTE-TO-PA Computational Analytics in SPODroutetopa
This document discusses applying computational analytics and social network analysis to SPOD data. It introduces concepts like centrality metrics, community detection algorithms, and dynamic graph analysis to study networks over time. Examples of social networks like friendships and email are provided. The document also discusses using the open-source Gephi tool to visualize networks and explore metrics. Overall, it explores how network analysis can provide insights from SPOD data to support tasks like identifying skilled users, encouraging participation, and understanding relationships between entities in the data.
Sexuality - Issues, Attitude and Behaviour - Applied Social Psychology - Psyc...PsychoTech Services
A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!
How to Scale Information Dissemination to the Virtual Digital WorkspaceXeniT Solutions nv
This document discusses how organizations can provide a unified search experience for remote workforces. It outlines how COVID-19 has increased remote work and impacted productivity. It then discusses how to transform workforces to the "new normal" by providing a single source of information through search. The rest of the document discusses solutions like Lucidworks Fusion to power search and analytics across structured and unstructured data sources. It also outlines Xenit's capabilities in integrating with Fusion to power search across Alfresco repositories.
The document outlines an agenda for a workshop on social innovation and enterprise at the 2015 Eastern Region AUTM meeting in Raleigh, NC. The workshop will include a panel discussion of experiences with social innovations from UNC Greensboro, University of New Hampshire, and North Carolina State University. Attendees will then break into groups to discuss case studies and paths to commercialization for social innovations. The goals are to analyze commercialization approaches for social innovations and develop best practices to sustain commercialization of non-traditional intellectual property for social benefit.
Protected Area Network Knowledge Management Framework (Needs Assessment and A...John Mauremootoo
PowerPoint presentation given at a consultative workshop to ascertain the knowledge management baseline among protected area stakeholders in Mauritius as a contribution to the development of a Protected Area Knowledge Management System.
This document provides an overview of key concepts relating to data and information strategies. It discusses different data types like categorical, ordinal, ratio and interval data. It also covers data structures, including structured and unstructured data. Big data and the increasing amount of data created is mentioned. The document explores how data can be analyzed and interpreted to inform strategic decisions and actions. It aims to help students understand and apply these concepts in the context of their own work.
Driving Change to Thrive in a Digital FutureNeil Calvert
Presented at Digital Transformation 2018 #DX2018, this presentation describes the power of enabling information literacy within your business and how this in turn creates opportunities to drive new business value and revenue in response to the expectations of today's consumers in the digital economy.
This document discusses knowledge management in projects. It begins by defining knowledge management and its importance in today's economy. It then discusses the types of knowledge, explicit and tacit, that are relevant to projects. The document outlines four stages of knowledge management development and notes the importance of managing knowledge in projects. It discusses key aspects of project management and the project life cycle where knowledge is generated and should be captured.
The document provides an overview of an event on emerging trends in data science given by Dr. Joanne Luciano. It discusses the data science workflow and various processes involved. Some key trends highlighted include increased use of AI and machine learning in data management and reporting, growth of natural language processing, advances in deep learning, emphasis on data privacy and ethics. The document also promotes the new minor in data science offered at University of the Virgin Islands, covering required courses and examples of course sequences for different disciplines.
The document discusses information systems and digital transformation. It covers topics like structured vs unstructured data, how businesses can leverage data and technology, and challenges around measuring success and the impact of digital initiatives. Examples are provided of how technology is changing work and forcing businesses to adapt. The document also outlines potential deliverables for a course, including a curation page, case study, and video presentation.
How to move Beyond-GDP? An action plannefwellbeing
BRAINPOoL (Bringing alternative indicators into policy) is an EU-funded project aimed at identifying and overcoming the barriers to ‘Beyond GDP’ indicators being used in policy.
Data-Driven Decisions: Unraveling Business Insights Through Research Data Ana...UnitedInnovator
Understanding the value of research data analysis for organisations is essential in the age of data-driven decision-making. This extensive guide digs into the area of decoding research data analysis and provides readers with key skills to elucidate insightful business information. Learn how to gather, arrange, and analyse data from various sources to spot trends, correlations, and patterns. Learn how to transform raw data into useful insight by utilising statistical analysis and data visualisation tools. This tool equips professionals with the tools they need to harness the potential of research data analysis and acquire a competitive edge in the quickly changing business environment of today. Its focus is on promoting informed decision-making.
Knowledge management simple secret of sucessfulSeta Wicaksana
Seta A. Wicaksana is a psychologist who works at Humanika Consulting. She has several roles including being a senior advisor at BPJS Ketenagakerjaan and deputy dean at the Faculty of Psychology at Pancasila University. She founded Humanika Consulting and writes books. She develops psychological assessment tools and trains, counsels, and assesses clients. She also teaches at Pancasila University and is pursuing her doctorate there in human resource management.
This document summarizes discussions from a conference on developing science, technology and innovation indicators and policies. Key topics discussed include:
- The need for a systems approach and measuring innovation in all sectors to better inform policy.
- Collecting new data on topics like scientist mobility, refugee migration backgrounds, and knowledge flows to answer important questions.
- Involving stakeholders like scientists, engineers and citizens to understand impacts through participatory processes.
- The limits of indicators and risks of oversimplification or perverse effects from misuse of metrics like rankings.
- Making indicators more inclusive by capturing contributions from new performers and geographical or cognitive areas not traditionally included.
- Opportunities and challenges of
A webinar by Fabrizio Pellizzetti, a Master Black Belt in Lean Six Sigma. In the first half Fabrizio thoroughly discusses what Lean Six Sigma is and the evolution of the methodology. In the second half, he dispels some myths surrounding LSS & clarifies real challenges before ending with the Lean Six Sigma Applicability.
Based on the ‘job track’ methodology developed at Lancaster University, the toolkit comes packed with resources to enable you to develop streamlined job families suitable to your IT organisation. The toolkit will enable you to produce clear information for individual staff to develop their IT careers, and to be supported along the way by their line managers. The toolkit includes a database of job descriptions, case studies and all the resources required to produce innovative and highly visual ‘job tracks’ in the style of an underground map. The pragmatic approach is simpler than a full SFIA implementation and is compatible with competency frameworks used in HE including HERA.
MVO in de tertiaire sector, door Freddy Noris, Sustainable Development Manage...Agoria
This document summarizes a presentation on CSR (corporate social responsibility) at SWIFT. It discusses how SWIFT's CSR program began in 2008 with a focus on environmental initiatives, employee engagement, and acting as a CSR facilitator for the financial industry. It outlines SWIFT's current CSR strategy and how this will impact expectations for its maintenance service suppliers, requiring them to meet ethical and environmental standards. The presentation concludes that CSR must be fully endorsed, embedded in a company's strategy and DNA, and sees it as a source of innovation, competitive advantage, and continuous improvement.
Brief description of ONA (Organizational network analysis) followed by a summary and comparison of the emerging SAAS vendors who provide support for network surveys and analysis.
This document discusses public-private partnerships (P3s) for infrastructure delivery, specifically for transportation projects. It analyzed 8 case studies of past and current P3 transportation projects using qualitative comparative analysis and stakeholder network theory. The analysis aimed to better understand outcomes of P3s and how to manage perceptions of stakeholders. Initial results pointed to need for further methodological refinement to identify clear relationships between factors and outcomes of successful P3 development and delivery. Defining specific measures of success is still being determined but may include meeting schedules for requests for proposals, financial close, construction milestones, and traffic volumes.
ROUTE-TO-PA Computational Analytics in SPODroutetopa
This document discusses applying computational analytics and social network analysis to SPOD data. It introduces concepts like centrality metrics, community detection algorithms, and dynamic graph analysis to study networks over time. Examples of social networks like friendships and email are provided. The document also discusses using the open-source Gephi tool to visualize networks and explore metrics. Overall, it explores how network analysis can provide insights from SPOD data to support tasks like identifying skilled users, encouraging participation, and understanding relationships between entities in the data.
Similar to Semantic Modelling - Paper presentation (20)
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A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!
Microbial interaction
Microorganisms interacts with each other and can be physically associated with another organisms in a variety of ways.
One organism can be located on the surface of another organism as an ectobiont or located within another organism as endobiont.
Microbial interaction may be positive such as mutualism, proto-cooperation, commensalism or may be negative such as parasitism, predation or competition
Types of microbial interaction
Positive interaction: mutualism, proto-cooperation, commensalism
Negative interaction: Ammensalism (antagonism), parasitism, predation, competition
I. Mutualism:
It is defined as the relationship in which each organism in interaction gets benefits from association. It is an obligatory relationship in which mutualist and host are metabolically dependent on each other.
Mutualistic relationship is very specific where one member of association cannot be replaced by another species.
Mutualism require close physical contact between interacting organisms.
Relationship of mutualism allows organisms to exist in habitat that could not occupied by either species alone.
Mutualistic relationship between organisms allows them to act as a single organism.
Examples of mutualism:
i. Lichens:
Lichens are excellent example of mutualism.
They are the association of specific fungi and certain genus of algae. In lichen, fungal partner is called mycobiont and algal partner is called
II. Syntrophism:
It is an association in which the growth of one organism either depends on or improved by the substrate provided by another organism.
In syntrophism both organism in association gets benefits.
Compound A
Utilized by population 1
Compound B
Utilized by population 2
Compound C
utilized by both Population 1+2
Products
In this theoretical example of syntrophism, population 1 is able to utilize and metabolize compound A, forming compound B but cannot metabolize beyond compound B without co-operation of population 2. Population 2is unable to utilize compound A but it can metabolize compound B forming compound C. Then both population 1 and 2 are able to carry out metabolic reaction which leads to formation of end product that neither population could produce alone.
Examples of syntrophism:
i. Methanogenic ecosystem in sludge digester
Methane produced by methanogenic bacteria depends upon interspecies hydrogen transfer by other fermentative bacteria.
Anaerobic fermentative bacteria generate CO2 and H2 utilizing carbohydrates which is then utilized by methanogenic bacteria (Methanobacter) to produce methane.
ii. Lactobacillus arobinosus and Enterococcus faecalis:
In the minimal media, Lactobacillus arobinosus and Enterococcus faecalis are able to grow together but not alone.
The synergistic relationship between E. faecalis and L. arobinosus occurs in which E. faecalis require folic acid
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Perhaps most importantly, Thermodynamics rapidly became a primary tool in the advance of applied science/engineering/technology, spanning micro-tech, to aerospace and cosmology. I can think of no better a story to illustrate the breadth of scientific methodologies and applications at their best.
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equations sourced by a topological defect, i.e. a singularity of a very specific form, the result is a localized gravitational
field capable of driving flat rotation (i.e. Keplerian circular orbits at a constant speed for all radii) of test masses on a thin
spherical shell without any underlying mass. Moreover, a large-scale structure which exploits this solution by assembling
concentrically a number of such topological defects can establish a flat stellar or galactic rotation curve, and can also deflect
light in the same manner as an equipotential (isothermal) sphere. Thus, the need for dark matter or modified gravity theory is
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at late times. Roughly 20 per cent of the stars in the prograde local stellar halo are associated with the observed caustics. Based
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measurement of phase mixing (2D causticality). The observed local phase-space distribution best matches the simulated data
1–2 Gyr after collision, and certainly not later than 3 Gyr. This is further evidence that the progenitor of the ‘last major merger’
did not collide with the MW proto-disc at early times, as is thought for the GSE, but instead collided with the MW disc within
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1. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Computational Intelligence
“A Framework to Investigate the Relationship Between
Employee Embeddedness in Enterprise Social Networks and
Knowledge Transfer” by Janine Viol and Caroline Durst
2. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Contents
● Introduction
● Knowledge Transfer
○ informal and formal
○ implicit and explicit
○ Limitation to enterprises
● Social Capital - bonding and bridging SN
● Measurement and data collection
○ Approaches to measure Knowledge Transfer
○ Strategies of Data Collection in SN
● Theoretical Framework
● Conclusion and Discussion
3. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Contents
● Introduction
● Knowledge Transfer
○ informal and formal
○ implicit and explicit
○ Limitation to enterprises
● Social Capital - bonding and bridging SN
● Measurement and data collection
○ Approaches to measure Knowledge Transfer
○ Strategies of Data Collection in SN
● Theoretical Framework
● Conclusion and Discussion
4. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Introduction
➢ Knowledge Transfer
● knowledge transfer influences productivity of an organization and is
“crucial for its survival”
● issues of the targeted research
○ knowledge transfer is often informal
○ to handle knowledge transfer in SN, it must be investigated and
understood
○ the process of knowledge transfer is difficult to be managed due to the
human factor (cultural differences, depth of social relationships, …)
5. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Introduction
➢ Research questions
● Research Questions
○ How are employees embedded in ESN?
○ How is this related to the company’s organigram?
○ How can social capital be identified and measured in ESNs using
methods of Computational Intelligence?
○ How is social capital associated with the knowledge transfer process of
individual employees?
○ How can the knowledge transfer get improved?
● Management Goals
○ Increasing productivity and team performance
○ Improving collaboration and reducing costs
6. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Contents
● Introduction
● Knowledge Transfer
○ informal and formal
○ implicit and explicit
○ Limitation to enterprises
● Social Capital - bonding and bridging SN
● Measurement and data collection
○ Approaches to measure Knowledge Transfer
○ Strategies of Data Collection in SN
● Theoretical Framework
● Conclusion and Discussion
7. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Knowledge Transfer
➢ Definition
“Sharing, interpreting, combining and storing of information.”
Argote et al.
8. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Knowledge Transfer
➢ Informal and formal
● informal
➢ knowledge transfer is not caused by business processes, but by
independent social interaction
● formal
➢ knowledge transfer is caused by business processes (e.g.
documentations, charts, business reports, ...)
➢ can be improved
9. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Knowledge Transfer
➢ Implicit and explicit
● implicit (tacit)
➢ knowledge transfer is caused by experience or observation
➢ “difficult to formalize and to communicate”
● explicit
➢ knowledge is transferred by a formalized, systematic representation
11. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Knowledge Transfer
➢ Limitation to enterprises
● entities in ESN are employees
● relations between entities can represent immaterial or material resources
● relation/tie strength is depended by
○ amount of time
○ emotional intensity
○ intimacy
○ reciprocal services
● influence of ESN on knowledge transfer
○ strong ties -> more efficient in transferring tacit knowledge ([Hansen])
○ both weak and strong -> explicit knowledge transfer
12. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Knowledge Transfer
➢ Differentiation of ESN
● formal ESN
○ management-directed and unit-based (e.g. wikis)
● informal ESN
○ emergent, user-directed and overlapping units
● working domain ESN
○ knowledge is directly related to the work
● non-working domain ESN
○ knowledge is indirectly related to the work (e.g. talks on company
excursions)
13. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Knowledge Transfer
➢ Differentiation of ESN
14. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Knowledge Transfer
➢ Seeking and giving advice
● 5 ways (according to Cross et. al.)
○ provision of solutions
○ meta-knowledge
○ problem reformulation
○ validation
○ legitimization
15. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Contents
● Introduction
● Knowledge Transfer
○ informal and formal
○ implicit and explicit
○ Limitation to enterprises
● Social Capital - bonding and bridging SN
● Measurement and data collection
○ Approaches to measure Knowledge Transfer
○ Strategies of Data Collection in SN
● Theoretical Framework
● Conclusion and Discussion
16. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Social Capital
➢ Definition
“Resources embedded in one’s social network, resources that can
be accessed or mobilized through ties in the network.”
Lin
17. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Social Capital
➢ Differentiation
● bonding networks
○ homogenous groups
○ similar interests
○ generation of emotional support
● bridging networks
○ heterogenous groups
○ non-redundant resources
○ better access to informational and instrumental resources
strong ties
weak ties
18. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Social Capital
➢ Examples
bonding
bridging
19. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Social Capital
➢ ESN influence
Ellison et al.:
● SN encourage both bonding and bridging social capital
● they allow people to generate new social capital (e.g. exchanging information
with new acquaintances)
● they allow to strengthen and maintain offline relationships
● large network of (weak) bridging ties improve the access to diverse
resources
➢ positive outcome
20. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Contents
● Introduction
● Knowledge Transfer
○ informal and formal
○ implicit and explicit
○ Limitation to enterprises
● Social Capital - bonding and bridging SN
● Measurement and data collection
○ Approaches to measure Knowledge Transfer
○ Strategies of Data Collection in SN
● Theoretical Framework
● Conclusion and Discussion
21. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Knowledge Transfer
Differentiation
● explicit knowledge is measured based on questionnaires or surveys
● implicit knowledge can be measured by observation or text analysis
Aspects
● sinks of knowledge
● sources of knowledge
● velocity
● viscosity
22. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Data Collection in SN
● approaches for measurements of implicit knowledge transfers
○ Movery et al. used citation patterns to detect the knowledge transfer
between companies
○ Huang and De Sanctis focused on forums and searched for the different
text patterns to categorize posts
➢ information seeking
➢ information providing
➢ explicit knowledge sharing
➢ implicit knowledge sharing
“Where can I find...?”
“Does anybody have...?”
“Do you know…?”
23. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Data Collection in SN
● assumptions in the paper
○ focus on explicit knowledge
○ knowledge transfer can occur in formal, informal networks in the
working and non-working domain
● steps for knowledge analysis
○ manually find knowledge areas (e.g. by functions)
○ (automatically) figure out levels of expertise by positions of employees
(extraction from SN profile pages)
○ find knowledge flow, sources and sinks e.g. by wall posts and comments
using pattern matching similar to the approach of the previous slide
24. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Data Collection in SN
● further steps
○ publishing of material (documents, links, ...) as an indicator for a
knowledge source
○ rating system for posted information to figure out usefulness and/or
quality
➢ What could be possible criterias for this? How could a reasoner
decide?
25. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
● short introduction into ego networks
ego
alter
26. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
network size
27. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
hierarchical positions/occupations in
ego’s network
28. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
measurement of social resources in ego’s network
29. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
● structural measures
○ How are actors in the network connected to each other?
○ analyze network size
30. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
ego
3
5
2
6
4
1
● small network size
● mostly egocentric
network
● network is constrained
by alters
bonding
31. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
● positional measures
○ reflect ego’s position in the (overall) network
32. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
ego
3
5
2
6
4
1
● ego is central
● ego has 5 connections,
one is bridging
➢ betweenness
● ego is close to each alter
● ego is well-connected to 2,
3, 5, 6
➢ eigenvector
● ego has two bridges, but
to single alters
33. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
ego
3
5
2
6
4
1
● example for a bridge to
other groups
➢ generate social capital
➢ diversity increases
opportunity of getting
new capital
34. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
● functional measures
○ focusses on network resources provided by specific ties
○ tie strength may be difficult to be extracted in ESN
➢ there are different approaches
35. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
● measuring tie strength - different approaches
○ Granovetter: measures amount of time, emotional intensity, intimacy,
reciprocal services
➢ How can we measure emotional intensity and intimacy?
○ other approaches include the analyzation of comments and messages in
SN
36. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
● measuring tie strength - fuzzy-logic approach
○ Arnaboldi et al.: analyzed twitter tweets using fuzzy logic with fuzzy set
➢ very low
➢ low
➢ medium
➢ high
➢ very high
○ on input parameters
➢ reply message percentage
➢ common follower percentage
➢ normalized mean reply delay
37. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
“Due to the similar functionalities of online social networks or
Twitter and ESN, the discussed tie strength indicators and the use
of a fuzzy logic approach can be assumed to be equally applicable
in ESN.”
Viol, Janine and Durst, Carolin
38. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Contents
● Introduction
● Knowledge Transfer
○ informal and formal
○ implicit and explicit
○ Limitation to enterprises
● Social Capital - bonding and bridging SN
● Measurement and data collection
○ Approaches to measure Knowledge Transfer
○ Strategies of Data Collection in SN
● Theoretical Framework
● Conclusion and Discussion
39. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
“Knowledge transfer processes are (...) the effects of different
social capital types”
Viol, Janine and Durst, Carolin
44. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Analysis of network structure
● high ratio means ego has access to many colleagues
➢ good access to social capital
54. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Analysis of network ties
55. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Analysis of network ties
● fuzzy-logic approach adapting Fazeen et al.
○ fuzzy-sets (very low, low, medium, high, very high)
○ four parameters
➢ common colleagues percentage
➢ shared project groups percentage
➢ reply message percentage
➢ normalized mean reply delay
○ best case: value of all parameters is very high
➢ high tie strength
60. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Analysis of social capital
● fuzzy-logic can be used
● indicators for bonding social capital
○ high network closure
○ strong ties
○ high degree of network homogeneity
● bridging
○ establish new links to more diverse resources and knowledge
62. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Knowledge transfer
● finding sinks and sources of knowledge
○ suggestion: text-mining approach by searching for patterns
○ Critics: Different people communicate differently.
“Where can I find...?”
“Does anybody have...?”
“Do you know…?”
63. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Final embeddedness
● embeddedness in the ESN influences social capital
● social capital influences knowledge transfer
● Han and Hovav: “bonding social capital positively affects knowledge sharing
and project performance”
64. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Achieved knowledge transfer
● approach is to calculate ratio of
○ number of information requests (information seeking posts)
○ number of responses (information providing posts)
● Can each response be seen as information providing?
65. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Contents
● Introduction
● Knowledge Transfer
○ informal and formal
○ implicit and explicit
○ Limitation to enterprises
● Social Capital - bonding and bridging SN
● Measurement and data collection
○ Approaches to measure Knowledge Transfer
○ Strategies of Data Collection in SN
● Theoretical Framework
● Conclusion and Discussion
66. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Conclusions
● framework enables researchers and practitioners to investigate knowledge
transfer process using social network analysis and methods of computational
intelligence
○ e.g.: identify “knowledge key individuals” and check if they match those in
the enterprise’s “key positions”
● outlook
○ analyze dynamics in ESN using swarm-intelligence and neuro-fuzzy
systems
67. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Conclusions
Thank you for your attention!
68. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Sources
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70. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Discussion
● What do you think? Do employees in higher positions tend to provide more
knowledge than others?
● What kind of social capital is more useful in software projects? Bonding or
bridging? Is the capital in the analyzed network the only important factor for
knowledge transfer?
● What do you think? Can you measure similarity between colleagues by
comparing their public ESN profiles?