
Social Networks
Authored by sylvia findlay
Business
University
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10 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Social capital is best described
Your individual skills and knowledge
The resources you can access through your connections with others
The financial assets you possess.
Your level of formal education.
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
The term "social networks" originated:
With the rise of social media platforms like Facebook
Primarily within mathematical graph theory in the late 20th century.
In the 1960s
With the study of organizational behavior in the 21st century.
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Social network analysis can be useful for
Making informal social structures explicit for study
Predicting stock market fluctuations
Designing new software applications.
Calculating an individual's human capital.
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
In the context of social networks, "degree centrality" refers to
An individual's ability to bridge different groups.
The shortest paths between individuals in a network.
An individual's position as a bottleneck in information flow.
The density of an individual's ties to others
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
"Betweenness centrality" in a social network indicates
Having many direct connections
Being close in proximity to many others in the network.
Being part of a cohesive group where everyone knows each other.
Acting as a bottleneck or bridge between different parts of the network
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Implementing divergent organizational change is often best achieved by change agents who
Are highly popular within a single cohesive group.
Primarily focus on incremental adjustments
Bridge different network clusters
Rely on peer pressure to implement changes.
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Implementing nondivergent organizational change is often more successful with change agents who are part of:
Fragmented networks with many structural holes.
Networks characterized by low trust among members.
Networks with high betweenness centrality but low degree centrality.
Cohesive networks where members are closely connected
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