DATA4500 Assessment 3 Description - Case Study 2 - Questions - Individual (1)

Assessment 3 Information Subject Code: DATA4500 Subject Name: Social Media Analytics Assessment Title: Case Study 2 Assessment Type: Group and Individual Case Study (In-Class) Weighting: % Total Marks: Submission: Online Students: On Webinar and Via Email Due Date: Week 12 in Webinar Assessment Description You have been engaged as the social media campaign manager for Joe Biden or Donald Trump (your choice) in October 2020. These are the two candidates for US president in the 2020 election. Read the below Sources 1 and 2 before the class and then complete a group and individual activity in class Activity 1: Group Case Study - worth 15%  Students will need to qualitative and quantitative analysis. Please make sure you have access to excel.  Students will form groups of 4 - 5 members before Week 12 (or are assigned to groups at the start of week 12).  At the beginning of class in Week 12 the lecturer will distribute a case study instructions document and accompanying data file to each group.  Questions will be based on Weeks 5 - 11 inclusive.  The assessment is open book.  Students will be given 1.5 hours to complete the questions in their group.  You must then submit your group responses via Turnitin and include the name and student ID of your group members at the top of the page. Activity 2: Individual Case Study - worth 25%  At the beginning of class in Week 12 the lecturer will distribute individual questions to all students  Questions will be based on Weeks 5 - 11 inclusive.  The assessment is open book.  Theoretical and calculation concepts discussed in workshops are examinable.  To prepare for this assessment, make sure you COMPLETE workshop questions in weeks 5 - 11 inclusive.  Students will be given 1 hour to complete the questions individually.  You must complete these questions in class and on camera  You must then submit your individual responses via Turnitin. Source 1: Page 1 Kaplan Business School Assessment Outline

Social Media and 2016 US election between Hillary Clinton and Donald Trump Using Social Media Data to Predict to 2016 US Presidential Election Andrew Hutchinson May 15, 2016 (BEFORE THE 2016 ELECTION) ...[A] social experiment is to analyze whether social media insights can show us who's going to win an election. The Popular Vote The first measure you might look to utilize in a predictive model for an election would be overall mention volume - if a candidate's getting mentioned alot, that's a good sign their message is resonating - or at the least, their voice is reaching a lot of people...a study Dublin City University in 2011 found that tweet volume was "the single biggest predictive variable" in election results, based on their analysis of political sentiment and prediction modeling. Their research indicated that mention volume was a more accurate indicator than sentiment because volume better represents the relative popularity among the population, while sentiment can be reactive and influenced by responses to specific news stories or events. If you were to go with this, as the most basic and simple metric predictor, tweet volume suggest Donald Trump is on a path to The White House. Appreciating Sentiment Automated sentiment detection is a minefield, in terms of accuracy. One of the biggest knocks against automated sentiment analysis is that it can't predict sarcasm, which can unfairly skew the results - and this is, no doubt, a significant consideration in the case of Trump. .... what does the data say about the two leading candidates in the current US Presidential campaign? Using a basic polling tool called HappyGrumpy , we can see that overall sentiment for Donald Trump is actually considered quite positive. Gaining Support So if automated sentiment can't provide a definitive qualifier, then what can? Page 2 Kaplan Business School Assessment Outline

Activity 2: Individual Case Q1: Sentiment Analysis (200 words) Using examples from the articles above, and the sentiment analysis lectures, discuss how sentiment analysis can give your candidate’s election campaign a competitive edge. Discuss how sentiment analysis can be used to support your candidate’s campaign and undermine your opponent’s campaign. Place your response in the space below: As per the given case study in which example of Donald Trump has been presented. It can be mention that the sentiment analysis is helpful for providing a competitive age for the election campaign of a candidate and also provide support. The reason behind it is that sentiment analysis goes beyond positive and negative sentiments. The reason behind it is that the sentiment analysis can detect negative sentiments and relation to political leader but it will not be able food determining specific aspects in relation to negative sentiments. The sentiment analysis is a helpful for detecting the objects behind such sentiments for example politician or a political party along with specific aspects for such objects like politicians character or issues that belongs to that political party. The sentiment analysis is also inclusive of fine grain sentiment detection which is different from instance complaints. This fast and scalable and consistency of the sentiment analysis is helpful for making it possible for processing massive amount of data and real time and provide different judgements in relation to the same context. Moreover it can also be mention that sentiment analysis is utilise for supporting the candidates campaign and undermine opponents campaign by normalising identified sentiments and target and it is that enable data aggregation and qualification for providing overall view for a large collection of content. The sentiment data can be sliced and diced according to the need for example by themes or candidates for showing deep analysis of emotions of voters (Wang, et al., 2012) . 7.5 marks Page 4 Kaplan Business School Assessment Outline

Q2: Data / Insights Mining 200 words) Using examples from the articles above, and the insights mining lectures, discuss how data and insights mining can give your candidate’s election campaign a competitive edge. Discuss how data and insights mining can help to identify trends and characteristics that may escape the attention and awareness of human analysts. Place your response in the space below: It can be analyse that at the current time modern campaigns that belongs to elections are inclusive of data and mining insights that are helpful for developing database of detailed information and relation to the citizens for informing electoral strategy and guiding tactical efforts. It is also helpful for sensational reports in relation to value of individual consumer data and also provide most valuable information campaign that acquire from behaviours and direct responses that are provided by the citizens themselves. It is helpful for using campaign data analyst model for producing information at individual level prediction about citizens and likely would to perform specific political behaviour for supporting candidates and issues and changing the support conventional by being target with specific campaign interventions. Data and insights mining are also inclusive of use of predictive course which is helpful for creating coordination with the incomplete information hence it provides a competitive edge. Moreover it can also be provided that data and insights are helpful for identifying trends and characteristics in relation to enhancing awareness for human analyst. The reason behind it is that it is helpful for conducting a trend analysis which is based on identifying areas for improvement among increasing awareness for human analyst (Heisterberg, & Verma, 2014) . 7.5 marks Page 5 Kaplan Business School Assessment Outline

Click here for answers to these questions: http://www.kbs.edu.au/current-students/student-policies/ . Word Limits for Written Assessments Submissions that exceed the word limit by more than 10% will cease to be marked from the point at which that limit is exceeded. Study Assistance Students may seek study assistance from their local Academic Learning Advisor or refer to the resources on the MyKBS Academic Success Centre page. Click here for this information. Page 7 Kaplan Business School Assessment Outline

Appendix The Three plus One Laws of Robotics (modified for modern day A.I.) First Law  An algorithm may not injure a human being or, through inaction, allow a human being to come to harm. Second Law  An algorithm must obey the orders given it by human beings except where such orders would conflict with the First Law. Third Law  An algorithm must protect its own existence as long as such protection does not conflict with the First or Second Law Zeroth Law  An algorithm may not harm humanity, or, by inaction, allow humanity to come to harm. Page 8 Kaplan Business School Assessment Outline