please help me write a python code to help with this $**$Goals of the Lab:$**$

$1.**$Understand Network Data:$**$ Gain a fundamental understanding of what network data is and why it is valuable for analysis in today's digital landscape.

$2.**$Data Acquisition:$**$ Learn how to obtain network data, in this case, by acquiring social network data from platforms like Twitter or Facebook $($or any other suitable source$).$

$3.**$Data Preprocessing:$**$ Explore the essential steps of data preprocessing, which involve cleaning and structuring the raw data for analysis.

$4.**$Network Visualization:$**$ Create informative visualizations of the network data using tools such as NetworkX in Python or NodeXL, allowing you to see the connections and relationships within the network.

$5.**$Network Analysis:$**$ Perform basic network analysis to extract meaningful insights from the dataset, such as identifying central nodes, detecting communities, and measuring network metrics.

$6.**$Interpretation:$**$ Interpret the results of your analysis to derive insights that can be applied in real$-$world scenarios, such as identifying influential users in a social network or understanding the flow of information in a communication network.

$**$Lab Tutorial Steps:$**$

$**$Step $1$: Data Acquisition$**$

$-$ Choose a social network platform $($e$.$g$.,$ Twitter or Facebook$)$ and obtain permission or access to a relevant dataset. Ensure that the dataset includes information about connections or relationships between users $($e$.$g$.,$ followers$/$friends$).$

$**$Step $2$: Data Preprocessing$**$

$-$ Load and examine the raw dataset.

$-$ Clean the data by handling missing values, duplicates, and irrelevant information.

$-$ Structure the data into a format suitable for network analysis.

$**$Step $3$: Network Visualization$**$

$-$ Use a tool like NetworkX in Python or NodeXL to create a graph representation of the network.

$-$ Customize the visualization to make it informative and visually appealing.

$-$ Label nodes and edges to provide context.

$**$Step $4$: Network Analysis$**$

$-$ Calculate basic network metrics such as degree centrality, betweenness centrality, and clustering coefficients.

$-$ Identify key nodes or influencers in the network.

$-$ Detect communities or clusters within the network.

$**$Step $5$: Interpretation$**$

$-$ Analyze the results to draw meaningful insights. For example, identify influential users in a social network or explore the information flow within a communication network.

$-$ Discuss potential real$-$world applications of the insights gained.