Graphs in social networks in Data Structures Theory - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the sentence to describe what a node represents in a social network graph.

Data Structures Theory

In a social network graph, a node typically represents a [1].

Drag options to blanks, or click blank then click option'

Aconnection between users

Buser or person

Cmessage sent

Dgroup chat

Attempts:

3 left

💡 Hint

Common Mistakes

Confusing nodes with connections or messages.

In social network graphs, nodes represent individual users or people.

2fill in blank

medium

Complete the sentence to explain what an edge represents in a social network graph.

Data Structures Theory

An edge in a social network graph represents a [1] between two nodes.

Drag options to blanks, or click blank then click option'

Aconnection or relationship

Bgroup membership

Cpost or comment

Duser profile

Attempts:

3 left

💡 Hint

Common Mistakes

Thinking edges are users or content instead of connections.

Edges represent connections or relationships between users in the graph.

3fill in blank

hard

Fix the error in the statement about directed edges in social networks.

Data Structures Theory

A directed edge means the connection goes from [1] to another node, but not necessarily back.

Drag options to blanks, or click blank then click option'

Aone node

Bboth nodes

Call nodes

Dno nodes

Attempts:

3 left

💡 Hint

Common Mistakes

Assuming directed edges mean mutual connections.

A directed edge shows a one-way connection from one node to another, like following someone.

4fill in blank

hard

Fill both blanks to complete the description of weighted edges in social networks.

Data Structures Theory

Weighted edges have a value [1] the edge to show the [2] of the connection.

Drag options to blanks, or click blank then click option'

Aassigned to

Bignored in

Cstrength

Dcolor

Attempts:

3 left

💡 Hint

Common Mistakes

Confusing weights with colors or ignoring them.

Weighted edges have a value assigned to show the strength or importance of the connection.

5fill in blank

hard

Fill all three blanks to complete the dictionary comprehension that creates a mapping of user names to their number of friends, filtering only users with more than 5 friends.

Data Structures Theory

user_friends = { [1]: [2] for [3] in users if users[[3]] > 5 }

Drag options to blanks, or click blank then click option'

Auser

Busers[user]

Dfriend_count

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up keys and values or using wrong variable names.

This comprehension maps each user to their friend count, including only those with more than 5 friends.

Practice

1. In a social network graph, what do the nodes usually represent?

easy

A. Posts or comments

B. Users or people

C. Groups or communities

D. Messages sent

Solution

1. Step 1: Understand graph components in social networks

   Graphs use nodes to represent entities. In social networks, these entities are usually users or people.

2. Step 2: Identify what edges represent

   Edges represent connections like friendships, not the nodes themselves.

3. Final Answer:

   Users or people -> Option B

4. Quick Check:

   Nodes = Users [OK]

Hint: Nodes = users, edges = friendships [OK]

Common Mistakes:

• Confusing nodes with edges
• Thinking nodes represent messages
• Mixing up groups with nodes

2. Which of the following correctly describes an undirected edge in a social network graph?

easy

A. It shows a mutual friendship between two users

B. It represents a user posting a message

C. It shows a one-way friendship from one user to another

D. It indicates a user joining a group

Solution

1. Step 1: Define undirected edge meaning

   An undirected edge means the connection goes both ways, showing mutual relationship.

2. Step 2: Apply to social network context

   In social networks, mutual friendship means both users are connected equally, matching undirected edges.

3. Final Answer:

   It shows a mutual friendship between two users -> Option A

4. Quick Check:

   Undirected edge = mutual friendship [OK]

Hint: Undirected edges mean two-way connections [OK]

Common Mistakes:

• Thinking undirected edges are one-way
• Confusing edges with user actions
• Mixing edges with posts or groups

3. Consider this simple social network graph represented as adjacency list:
{'Alice': ['Bob', 'Carol'], 'Bob': ['Alice'], 'Carol': ['Alice']}
How many direct friends does Alice have?

medium

A. 2

B. 1

C. 3

D. 0

Solution

1. Step 1: Read Alice's adjacency list

   Alice's list shows ['Bob', 'Carol'], meaning Alice is directly connected to Bob and Carol.

2. Step 2: Count direct friends

   There are 2 names in the list, so Alice has 2 direct friends.

3. Final Answer:

   2 -> Option A

4. Quick Check:

   Length of Alice's list = 2 [OK]

Hint: Count names in adjacency list for direct friends [OK]

Common Mistakes:

• Counting indirect friends
• Confusing keys with values
• Ignoring list length

4. Given this adjacency list for a social network:
{'Dave': ['Eve'], 'Eve': ['Dave', 'Frank'], 'Frank': ['Eve']}
What is wrong if we add 'Frank' to Dave's list but forget to add 'Dave' to Frank's list?

medium

A. The graph will have a syntax error

B. The graph will show no connection between Dave and Frank

C. The graph becomes directed, showing one-way friendship

D. The graph will crash when accessed

Solution

1. Step 1: Understand undirected graph rules

   In undirected graphs, edges must be mutual. Adding Frank to Dave's list but not Dave to Frank's breaks this.

2. Step 2: Identify effect on graph type

   This creates a one-way connection, making the graph directed for that edge.

3. Final Answer:

   The graph becomes directed, showing one-way friendship -> Option C

4. Quick Check:

   Missing mutual edge = directed edge [OK]

Hint: Mutual edges needed for undirected graphs [OK]

Common Mistakes:

• Expecting syntax errors
• Assuming no connection exists
• Thinking graph will crash

5. A social network wants to suggest new friends by finding users who share at least two mutual friends but are not directly connected. Which graph concept helps solve this problem?

hard

A. Calculating node degrees

B. Finding shortest paths between nodes

C. Detecting cycles in the graph

D. Counting common neighbors between nodes

Solution

1. Step 1: Understand the friend suggestion criteria

   The network wants to find users not directly connected but sharing at least two mutual friends.

2. Step 2: Identify graph concept matching criteria

   Counting common neighbors (shared friends) between two nodes helps find such pairs.

3. Final Answer:

   Counting common neighbors between nodes -> Option D

4. Quick Check:

   Mutual friends = common neighbors [OK]

Hint: Mutual friends = common neighbors count [OK]

Common Mistakes:

• Using shortest paths incorrectly
• Confusing cycles with mutual friends
• Only checking node degrees