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Tutorial Network Analysis Free University Berlin, SS 2016/17 Martin Vinson Alena van Bammel Assignment 2 Due date: 7.7.2017 9:00AM before the lecture Include all important steps of your calculations/solutions.

How to fill out tutorial network analysis

How to fill out tutorial network analysis

1. Step 1: Start by familiarizing yourself with the basics of network analysis.
2. Step 2: Identify the purpose of your analysis - are you trying to understand the connections between individuals or organizations?
3. Step 3: Gather the required data for your analysis. This may include information about nodes (individuals or organizations) and edges (relationships between nodes).
4. Step 4: Preprocess your data by cleaning it, removing any duplicates or errors.
5. Step 5: Choose the appropriate network analysis method based on your research question. Some common methods include centrality analysis, community detection, and link prediction.
6. Step 6: Apply the chosen method to your data and analyze the results. Visualize the network to gain insights and identify patterns or trends.
7. Step 7: Interpret the findings and draw conclusions from your network analysis.
8. Step 8: Document your analysis process and results in a tutorial format, ensuring that it is clear and easy to understand for your target audience.

Who needs tutorial network analysis?

1. Researchers in the field of social sciences who want to study relationships and interactions between individuals or organizations.
2. Business analysts who need to understand the network structure and connections between employees, customers, or suppliers.
3. Marketing professionals who want to identify influencers or key individuals in a social network.
4. Policy makers who are interested in understanding networks of influence or collaboration within a specific domain.
5. Security analysts who need to analyze connections and patterns to detect potential threats or vulnerabilities.
6. Students or individuals interested in learning about network analysis as a skill for data analysis and visualization.

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