This is a SOCIAL MEDIA ANALYSIS/Computer science ONLINE EXAM scheduled Monday 11/1/2021 from 15:30 to 17:30 Irish timeA 2 hours Exam with NO time extension.
Please see attached previous year exam papers for better preparation.Please help me get high grades. This is my 3rd order in 2 days
Question 1 (33 Marks) a. Performing an analysis of the communication patterns within an organisation can help identify issues that inhibit the effective flow of information. Describe three such issues, and explain how they can be identified using SNA software such as Node XL. Use a diagram to illustrate your answer. (15 Marks) b. Consider the table below, which shows an extract from an email log of an organisation. How would you transform this data into a form suitable for SNA? In your answer, you should consider how to treat multiple emails between people, and how the emails to people in the “cc” field should be handled. (10 Marks) c. Given that an email log will contain vast quantities of data, describe two means by which you could present a network graph which displays only the most important communication actors and links. (8 Marks) Question 2 (33 Marks) a. The languages HTML and XML are not suitable tools for publishing data on the web. Using examples explain why this is the case. Explain, using an example, why the RDF language is an adequate medium. (10 Marks) b. Describe three of the principal features of the RDFS language. Use an example to illustrate these features. (9 Marks) c. What is meant by an “ontology language”? Explain the differences between the RDFS and OWL languages. (10 Marks) d. Using the DBPedia project as an example, describe the value of publishing data on the web. (4 Marks) Question 3 (33 Marks) a. State and explain the the four network metrics used to measure different aspects of a social network graph. (12 Marks) b. What is meant by the terms (i) hub and (ii) bridge. Using only the node metrics, describe how you could tell if a node was a hub or a bridge. (8 Marks) c. Describe the conditions under which it may be disadvantageous to have a node in a (i) hub position or a (ii) bridging position. In each case, describe why it may be disadvantageous and state how the problem may be resolved. (6 Marks) d. Analysing content is key to achieving a deeper understanding of a social network. Describe the four steps you would take to analyse the content of a social network, using an example to illustrate your answer. (7 Marks) Question 4 (33 Marks) a. Describe three characteristics each of “strong ties and “weak ties” in a social network. Using only the structural characteristics of the network, how would you determine whether a tie could be considered “strong or “weak”? (10 Marks) b. Describe two features which use the content of messages as predictors of tie strength. In each case, give two examples of how these factors can be inferred from a given network. (6 Marks) c. Why are epidemic models useful when modelling the spread of information in a social network? (5 Marks) d. Explain the SIR model of information propagation in a social network. Give an example of how it can be applied to a scenario such as viral marketing. State three deficiencies of this model. (12 Marks) Question 1 (33 Marks) a. The analysis of a Social Media network can help us identify important nodes. Explain what is meant by an “important” node. Use examples to demonstrate why there can be multiple interpretations of the importance of a node. (5 Marks) b. What is a metric, in relation to Social Media analysis? Describe the four principal node metrics which you could use in order to undertake Social Media analysis. (10 Marks) c. What is meant by an “Egocentric Network”? What are the differences between a 1-degree, 1.5-degree, and a 2-degree egocentric network? Why are higher degree egocentric networks seldom used? (8 Marks) d. Define the following, and describe how each is calculated (i) the Density of a network (ii) the Local Clustering Coefficient of a node State one useful piece of information that we can learn from each of these measures. (10 Marks) Question 2 (33 Marks) a. What is meant by the term “Semantic Web”? State two advantages of the Semantic Web when compared to the “traditional” web. (6 Marks) b. Explain the purpose of the following Semantic Web languages: RDF, RDFS and SPARQL. Using an example in each case, show how they serve to achieve the goals of the Semantic Web. (15 Marks) c. Why are epidemic models useful when modelling the spread of information in a social network? Describe the SIR compartmental model of information propagation and explain 2 deficiencies of the model. (12 Marks) Question 3 (33 Marks) a. What is meant by the terms (i) strong ties and (ii) weak ties in a social network. State three features of each. Describe a circumstance under which it can be useful to distinguish between strong and weak ties. (12 Marks) b. Why is it necessary to predict tie strength? Describe two features in a social network that can be used as predictors of tie strength. (6 Marks) c. Describe the four steps which can be used to analyse the content of a social network. (8 marks) d. Illustrate how you would follow the steps described in part (c) above, in order to analyse the network below, given that it represents a 1.5 degree network of a Twitter user. Nodes are users and edges represent follower/following relationships. The ego is not shown. State any assumptions you make. (7 Marks) Question 4 (33 Marks) You are an analyst who has been asked by an organisation to identify the impediments to information flow and communication among its employees. The organisation chart is shown in Figure (a). To help conduct your analysis, you examine the principal email communications between employees. This is shown in Figure (b). Compare the figures and answer the questions below. Fig. (a) Organisation Chart Fig. (b) Email communication chart a. Identify three issues that you see as roadblocks to communication in the organisation. (9 Marks) b. Describe four visual features that could be used in a Social Network graph, which would help to distinguish between different categories of users, or to highlight important users. (12 Marks) c. What is meant by the terms (i) filtering and (ii) motif simplification? Given that the number of emails may be very high, describe how you could apply filtering and motif simplification to highlight the important features of this network. (12 Marks) Question 1 (33 Marks) a. What is meant by (i) the density of a network and (ii) the Local Clustering Coefficient of a node. Using a simple example, explain how each would be calculated. (10 Marks) b. Explain why a node with a high Local Clustering Coefficient may be less valuable for the purposes of information dissemination through the network. Give an example to illustrate your answer. (9 Marks) c. Consider the following network and answer the following questions. It is difficult to visualise the most important features in the network diagram as it is presented. (i) Explain how you would use the graph metrics to highlight nodes that are “important”. (7 Marks) (ii) Explain how you would simplify the graph in order to highlight the key structural characteristics (rather than the detail of the nodes themselves). (7 Marks) NB: It is not necessary to attempt to redraw the network in your answers. Question 2 (33 Marks) a. Explain the SIR model of information propagation in a social network. Give an example of how it can be applied to a scenario such as viral marketing. State three deficiencies of this model. (15 Marks) b. Why is it useful to measure tie strength in a social network? (4 Marks) c. How would you determine whether a tie could be considered “strong or “weak”? What is the difference from an information propagation perspective? (8 Marks) d. Intimacy, relationship intensity and social distance are three factors which can be used to predict the strength of a tie in a social network. In each case, give two examples of how these factors can be inferred from a given network. (6 Marks) Question 3 (33 Marks) Organisational email network data sets can provide important information on information flow and communication patterns. a. Describe how you would represent a small email network graph (consisting of 50 individuals and 1000 messages) using software such as Node XL. (6 Marks) b. State four challenges you would face in the construction of an email network dataset for a large organisation. (8 Marks) c. An email network dataset could be used to reveal important information related to both individuals and departments within an organisation. - Describe two such pieces of information related to individuals. In each case state how the information could be inferred from the graph metrics. (8 Marks) - Describe three such pieces of