A major part of your coursework assessment is the group project. The goal of this project is to come up with an interesting business (or social, environmental, or political, etc.) problem (topic, trend, or issues) and solve (investigate, or elaborate) it using social media data. This will require you to carefully collect and analyse social media data using the knowledge, tools, and skills that you have developed in class. You will be required to produce evidence to support any of your claims. Your team will be required to submit a written report at the end of the semester.
Ideally, we should be able to take away some generalisable lessons from your work. For example, in this blog post, using the data collected from Twitter using NodeXL, Khan (2016) analysed Malcolm Turnbull and Bill Shorten’s (Australia’s top two Prime Ministerial candidates at that time) Twitter presence to contrast and compare them in terms of interactivity, influence, and popularity. Khan (2016) found that over Twitter, Turnbull is more interactive and popular, whereas, Shorten is more influential.
You should choose an event (such as a news item) and try to study how it was reacted to in social media. For example, you might study a #tag on Twitter around a specific event (a conference, a global event, a trending TV show, a new product launch, or sporting event). Or you may research who are the key influencers? What are the customer perceptions of a brand and its competitors? The impact of key market events (e.g., competitive new product launches) on a brand, etc.
Be creative! I encourage you to discuss your ideas with me, so we can iterate to a good project.
Keep in mind that you would not simply describe what happens (though that would be included), but also try to understand what your analysis of that one event means for understanding similar events more broadly (known as the generalisation of finding in academia).
Regardless of the topic you choose, your analysis must include some sort of visualisation of the data (e.g., network, heat-map, words cloud, etc. I personally prefer network visualisation).
A team cannot have more than 6 or less than 4 members.
Through the semester you will be involved in comprehensive discussions and tutorials on how to obtain and analyse a variety of social media data (including network, text, hyperlinks, actions, search engine, geo-data, etc.). You are expected to use multiple different tools top prepare your report. So completing this assignment will only be limited by your imaginations.
A common structure for your report will be:
1. Title of the report and Abstract (a short summary up to 500 words)
2. Introduction section (what you want to investigate and why is it important to investigate?)
3. Research question (s) (what you want to know?)
4. Related work (an overview of the previous work that other researchers have work on similar topics if any; hint: search library online databases for research articles on your topic).
5. Methodology (How would you answer the research question(s)?)
6. Discussion (explain what you found and the broader lessons/recommendations that can be drawn from it).
7. Conclusions
8. Reference list: provide a full APA style reference list including hyperlinks for all and any resources used in your report. You should also provide the name of the tool used to conduct your analysis and to produce your visualisations (place this information near the images in your report).
· The final report should be no more than 3,000 words (excluding tables and references),
· 12-point font for the main text, and 1.5 line spacing.
· 30mm margins all around,
· You may add figures and summary tables into the appendix, however I prefer that they are included in the body of your report. Large data tables should be presented in an appendix,
· Include page numbers, headings and subheadings to facilitate the review.
· Literature cited should follow APA style references both in text and in the reference list.
The paper will be graded based on the following criteria:
· Is the team focused on an interesting problem/question? (10%)
· To what extent the team succeeds in solving (elaborating) the issue with social media data? (30%)
· Is the report theoretically and methodologically sound? (20%)
· Does the report include meaningful visualisations of the data (20%)
· Writing composition (grammar, spelling, logic, and ease of reading) (10%)
· APA style references both in-text and as a complete reference list at the end of the report (10%)
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