ASSIGNMENT 2: TEXT ANALYSIS OF PROPOSAL FOR DISNEYLAND EDINBURGH
Assignment 2 (Worth 50%)
Submission: 11am Mon 9th January 2023. A 2500 word Report, associated Orange Workflows and Data files.
This assignment requires you to develop a real-world text analytics solution that will be capable of instigating change in an organisation. You have already participated in an organisational task from a group perspective, and have specified a project in CRISP-DM. You will now deliver a text analytic solution.
Your task is to adopt your provided project plan and to pursue the text analysis that is specified. You are to perform the Data Preparation, Modelling and Evaluation as part of the CRISP-DM strategy prepared for Disney as they seek to prepare for the best and worst issues that will arise, relating to a Disneyland Edinburgh, and to support Disney in understanding opportunities and threats that surround the project.
You are to submit a report to Disney presenting Five Text Analysis stories that offer compelling evidence for adopting five different strategies. The five strategies are expected to be persuasive, and aimed at supporting Disney as it decides on whether or not to invest an estimated $1billion to establish a Disneyland Edinburgh.
You are specifically asked to address pressing questions of sustainability and risk management as Disney pursues a strategy. In doing so, you will help the Disney to reflect on important considerations they will need to be addressed before taking the proposals forward.
Text Analytics Project Specification
You are to lead Disney decision-making by asking the company to focus 5 themes chosen from a range of relevant topics and sentiments brought up by previous customers. You can focus wholly on customer topics and sentiments as defined in the answers to survey questions on the three Disney lands that already exist. Or you can mix and match some of the survey observations with others that you consider important, perhaps from Twitter. You should guide Disney through key positives and the negatives that you discover, so that they can address both opportunities and threats.
You are to design and develop a series of Orange Workflows of your choice for Disney using Text Analytics implemented in Orange Data-Mining. In addition, you are to write a report that is to be supplied with the workflows and data in answer to the project brief. You are also asked for a brief set of user guidelines showing how to use the workflows.
Each theme you chose should be analysed, using the story-telling, and each analysis should be capable of leading Disney decision-making.
Submitted Report: Using The Storytelling Framework for each of your Five Analyses
You should produce a suitable report, as described in our materials on report writing. The Main Body of the report should have five main sections, one for each of the analyses you have performed.
Figure 1: The Story-Telling Framework
Five Orange Workflows
Your Orange work should contain five Orange Workflows, each of which should support one of your Text Analytics stories.
Working with data
You should submit the Orange Workflows all associated data files along with your report in a zipped file.
- Using the Disney dataset along with any other that you may have identified on Twitter, identify five compelling text analytics narratives that can inform Disney policy in deciding whether to establish a Disneyland Edinburgh.
- Present your results in a 2,500 report that contains:
a. Title Page
b. Executive Summary
c. Table of Contents
e. A Main Body which includes
i. A section on Data Preparation
ii. The Five Key Analyses, (some details may be placed in an appendix)
iii. Use screen shots from your Orange Data-Mining work to highlight important points, provide
iv. Key recommendations for each narrative, and
v. Analysis of any pressing questions of disruption, sustainability, risk management or data ethics that need to be addressed in each narrative.
f. A short user guide on how to use each of the workflows in Orange.
g. Recommendations and Conclusion, along with any necessary appendices.
- Recommendations and Conclusion, along with any necessary appendices.
- Submit your Orange files, and any Data Files.
Archive all of the files together (using zip) and submit the archived file in Canvas. Highlight the file you wish to submit in your home directory (use the students’ home directory icon for this). If you wish to make changes to a submitted file, just re-submit the amended version. The file with the latest date will be marked.
Please keep a backup of your file. Further details of the marking criteria can be found on the marking sheet which is in the module outline.
Tom Kane, November 2022
Get expert help for Text Analytics for Business and many more. 24X7 help, plag free solution. Order online now!