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Introduction

Social network analysis (SNA) has become an essential tool for understanding the dynamics of customer support communities and knowledge sharing in today’s digital age. As companies strive to provide effective support and foster collaboration among their customers, SNA offers a unique perspective on how individuals interact, share information, and influence one another within these online communities. By examining the structure of these social networks, researchers can identify key influencers, information hubs, and communication patterns that drive the success of customer support initiatives.

This thesis explores the application of social network analysis in the context of customer support communities and knowledge sharing. By leveraging network theory and analytical techniques, we aim to uncover insights that can enhance the effectiveness of customer support strategies and improve knowledge sharing practices within online communities. This research not only contributes to the academic understanding of SNA in a business context but also provides practical implications for companies looking to optimize their customer support efforts.

Chapter 1.1: Introduction
1.2: Background of study
1.3: Problem Statement
1.4: Objective of study
1.5: Limitation of study
1.6: Scope of study
1.7: Significance of study
1.8: Structure of the Thesis
1.9: Definition of terms

Chapter 2: Literature Review
– Theoretical foundations of social network analysis
– Customer support communities and knowledge sharing
– Relationship management in online communities
– Key metrics and measures in social network analysis
– Influence and information diffusion in social networks
– The impact of network structure on customer support outcomes
– Best practices for fostering collaboration in online communities
– Challenges and opportunities in applying SNA to customer support

Chapter 3: Research Methodology
– Research design and approach
– Data collection methods
– Sampling techniques
– Data analysis procedures
– Ethical considerations
– Validity and reliability of findings
– Data visualization techniques
– Software tools for conducting SNA

Chapter 4: Discussion of Findings
– Overview of the social network structure in customer support communities
– Identification of key influencers and information hubs
– Analysis of communication patterns and knowledge sharing behaviors
– Comparison of different customer support strategies
– Implications for improving customer support initiatives
– Practical recommendations for companies

Chapter 5: Conclusion and Summary
– Recap of key findings
– Contributions to theory and practice
– Limitations of the study
– Future research directions
– Concluding remarks

Thesis Overview

In this thesis, we investigate the application of social network analysis in customer support communities and knowledge sharing. Our research aims to uncover insights that can enhance the effectiveness of customer support strategies and improve knowledge sharing practices within online communities. By analyzing the structure of social networks, we identify key influencers, information hubs, and communication patterns that drive the success of customer support initiatives.

Chapter 1 provides an introduction to the research topic, outlining the background, problem statement, objectives, limitations, scope, significance, structure of the thesis, and definition of key terms. Chapter 2 presents a comprehensive literature review on social network analysis, customer support communities, knowledge sharing, relationship management, metrics, influence, network structure, and best practices. Chapter 3 details the research methodology, including design, data collection, sampling, analysis, ethics, validity, reliability, visualization, and software tools.

Chapter 4 discusses the findings of our study, including an overview of social network structures, key influencers, communication patterns, knowledge sharing behaviors, comparison of support strategies, implications, and recommendations. Finally, Chapter 5 offers a conclusion and summary, highlighting key findings, contributions, limitations, future research directions, and concluding remarks.

Overall, this thesis contributes to the understanding of social network analysis in the context of customer support communities and knowledge sharing. It offers practical insights for companies looking to optimize their customer support efforts and improve collaboration within online communities. By leveraging SNA techniques, organizations can better understand the dynamics of their customer networks and enhance their support strategies accordingly.

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