This project is in an open-book format. You can refer to any material available to you. However, your primary attention should be given to the materials discussed in class, as opposed to other web resources (e.g., Wikipedia).
· Formatting guideline:
· Page limit: 5 pages in total. References, tables and figures do not count towards the page count.
· Use either Times New Roman (12 font size) or Ariel (11 font size); double-space; at least 1-inch margin on all sides.
· Every material you referred to must be listed in the bibliography attached to the end of your paper. Any reference style is acceptable.
1
Overarching grading rubric
· Your answers must closely reflect the content discussed in this course.
· Your answers must be comprehensive. In other words, partially answering questions will not get you the full grade.
· Refrain from copying random content you found on the web (e.g., Wikipedia). Vague answers, such as, “because everyone is connected through social media…” will not earn you any credit.
· You will earn 100% of the grades assigned to a question if your answer covers the entire content pertinent to the given question in the textbook, lectures, and recitations.
· E.g., What are the reasons for triadic closure?
· Your textbook lists 4 reasons over Chapters 3 and 4, and you listed all 4.
· You will earn 80% of the grades assigned to a question if your answer covers only partial content pertinent to the given question in the course materials (e.g., textbook, lectures, and recitations).
· E.g., What are the reasons for triadic closure?
· Your textbook lists 4 reasons over Chapters 3 and 4, but you listed only three.
· You will earn 50% of the grades assigned to a question if your answer does not cover any material pertinent to the given question in the course materials (e.g., textbook, lectures, and recitations) but is based on the content you found on the web or common sense.
· E.g., What are the reasons for triadic closure?
· Your textbook lists 4 reasons over Chapters 3 and 4, but you listed none of these but list some information you found on Wikipedia.
*** Beginning of the Questions *** Chapter 1
1. Why is observing and describing a social network at the population level, as opposed to the individual level, necessary? What benefits does the population-based analysis of a social network provide to us? What are *at least* four important network dynamics that can be studied at the population level? Describe each network dynamic and give at least one example of EACH of the four network dynamics you can find in the real world. (a total of 4 network dynamics, and a total of 4 examples [1 example per network dynamic]). (10 points)
Chapter 2
2. Using Nodes and Edges, draw a graph that has a node that is a gatekeeper for other nodes. You can either draw a graph on another sheet of paper, take a picture, and include in your answer, OR you can use the shapes in the word processing software. Either way, make sure that your handwriting or text in the figure is clearly legible to the grader. If we can’t read your text, we cannot give you full credits. This figure will not count towards the page limit. (5 points)
TomFigure 2.8. Breadth-first search, Page 30 in your textbook
2.1 Based on the figure to the left, explain what breadth-first search is and how you would measure the distance between “you” and “Tom”. Then, explain what implications, benefits, and lessons the breadth-first search bring to you. A well-known example of a lesson learned from conducting breadth-first searches is the discovery of a “small world phenomenon” where everyone in the world is connected with <7 distance. Do NOT use this example of a small world phenomenon. List another, different example of benefits of performing breadth first search and calculating distance. 5 BONUS POINTS: if you find an example usage of breadth-first search in an academic article published in a peer- reviewed journal. (10 points)
Chapter 3.
3. Consider the graph on the right, in which each edge — except the edge connecting b and c — is labeled as a strong tie (S) or a weak tie (W). According to the theory of strong and weak ties, with the strong triadic closure assumption, how would you expect the edge connecting b and c to be labeled? Give a brief (1-3 sentence) explanation for your answer (5 points)
3.1 Problem 2 – In the social network depicted below in Figure 3.23 with each edge labeled as either a strong or weak tie, which two nodes violate the Strong Triadic Closure Property? Provide an explanation for your answer (5 points).
3.2 Explain why most people get information about their jobs from acquaintances not from close friends/family members based on the notion of “strength” of weak ties. Make sure you explain what a weak tie is, why/how a weak tie is formed (using strong triadic closure property), and what benefits accrues from the triadic closure property. You can find a partial answer to this question in Figure 2.8. Reading this entire chapter and the lecture notes (“Eureka!” slides) will give you two sets of reasons. Mention these two sets of reasons explaining from strength of weak ties. (15 points)
Chapter 4.
4 Explain how Christaki and Fowler found that obesity is contagious. Identify the three sets of factors they tested (listed in your textbook page 83, Chapter 4 lecture notes as well as Ted- Talk shown during the lecture), and illustrate how they used the homophily test to conclude that obesity is contagious and what mechanism underlies the contagion. Be sure to refer to the homophily test that was used to assess if the plot (Figure 4.2) exhibits homophily in your textbook. Be sure to modify the variables (or parameters) in this homophily test to be applicable to the assessment of homophily in the contagion of obesity. Then, explain what underlying mechanism Christaki and Fowler have suggested to explain the contagion of obesity. Which mechanism—either social influence or selection—explained the contagion of obesity? (15 points)
4.1 Given a network showing pairs of people who share activities, we can try to reconstruct an affiliation network consistent with this data. For example, suppose that you are trying to infer the structure of a bipartite affiliation network, and by indirect observation you’ve obtained the projected network on just the set of people (refer to Exercise 2 page 105, and discussed in the recitation October 1st). There is an edge joining each pair of people who share a focus. This projected network is shown below in Figure 4.22.
– Draw an affiliation network involving these six people, together with four foci that you should define, whose projected network is the graph shown above in Figure 4.22. (10 points)
Chapter 5.
5 For the diagram below in Figure 5.4, Assuming that the network is balanced, please answer why the question marks are positive or negative. (5 points)
5.1 In the Labeled Graph below, please explain if the graph is balanced or unbalanced in 1-2 sentences. (5 points)
5.2 Describe how you would use structural balance theory if you were to develop an automatic recommender system for products for your customers. Automatic and intelligent recommender systems generate and suggest products that customers are likely to purchase, based on the structural balance of a social network as presented in Qi et al.’s paper (to be shared during the lecture on October 6th). (15 points)
L. Qi et al., ‘‘Structural balance theory-based e-commerce recommendation over big rating data,’’ IEEE Trans. Big Data., Sep. 2016, doi: 10.1109/TBDATA.2016.2602849.
You do not need to understand the programming code or equations in this article. Focus on their ideas about how to use structural balance theory in order to increase the accuracy of their recommendations (i.e., the likelihood that their recommended products are purchased by the customers).
*** End of the
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