- Individual Interdisciplinary project with assessment
Choose an individual project from the list below, as discussed individually in the class to met your skill set, research the topic and define the problem your solution addresses, define your algorithm or analysis method, develop the solution (data analysis, mapping), and write a 3,000 word report including images, graphs or screenshots demonstrating the outcome of your solution. Include bibliographic references from your research to back up your arguments. The word count is all inclusive, 10% allowance (2,700 – 3,300) is permissible (excluded references).
Submit the developed solution and results in a readable format (graphs, maps, code screenshots, tables, including code description) and the report via Moodle by Monday 6th January 2022.
- Cover page (include your candidate number/title/ word counts)
- Table of content
- Briefly introduce your research question
- Give a description of your report structure
- Literature review (with 25-30 references; provide background of the problem; all arguments should be supported by references)
- A detail description of your methodology (provide reference to your methods and data)
- Define your algorithm or analysis method, develop the solution (data analysis, mapping)
- Describe your result with screenshot/output (with tables, charts, maps, or figures)
- Discuss the result
- Outline the limitations of the data and approaches
- Discuss the opportunities and challenges for digital public health, and the potential applications for this area
(To be discussed in class.)
(a) Problem definition (clarity and relevance of the problem): 20%
(b) Project solution (algorithm, working implementation, results correctness and creativity): 50%.
(c) Report (content, information correctness, structure, flow, language, and grammar): 30%
Minus 10% of the pre-penalty mark if the report is outside the word limit, but this penalty cannot change your mark from a pass to a fail.
Vaccination debate on Twitter
Research how Twitter is increasingly providing a wide reaching social media for distorted arguments about vaccination spread by anti-vaccines pressure groups.
Download Twitter datasets from
debating the HPV vaccine controversy in 2015-2016 and analyse the Tweets using a SW package of your choice (ML classifier, database package, R, statistical / mixed methods in excel, etc) – try to identify themes, geographic coverage and focus on pro/against users around pivotal events – e.g. situation in Japan and Ireland, or other.
In your report, discuss the importance of vaccination from public health perspective and the role mass media have been playing in contradicting the public health message. Discuss the importance of the ‘MMR vaccine causes autism’ misinformation in 2000, focus on the role Internet and recently social media have played in corroding public confidence in vaccination and propose ways forward.
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