In this individual assignment, you are to extract (or select) a dataset from a social media of your choice and employs exploratory data analysis techniques to study a real-world social media mining / analytics topic.
This assignment contains two stages. In the first stage, you need to decide a topic to study and pick a dataset from either data.world or kaggle. The selected dataset should contain at least 5 attributes (including user text comments) for analysis. You are strongly encouraged to discuss with your instructor about the chosen dataset beforehand. In the second stage, you need to conduct data analysis on the selected dataset and write a report on your findings with an explanation of your source code. Your report,source code, and the video URL should be submitted to the OLE by Apr 14 (Fri) 5pm. Please hand in your work early as the OLE is often busy around the deadline. Note that 10% of the marks awarded to the assignment will be deducted for every calendar day overdue.
Grading Criteria: This individual assignment will be graded based on the following components:
Part A: Choosing Topic (10 marks)
Discussion with the instructor about the proposed topic: 5 marks
The appropriateness of the chosen dataset: 5 marks
Part B: Source code for data analysis (40 marks)
Correctness: 10 marks
Exploratory data analysis: 20 marks
o Basic statistics: average, median, frequency count, etc.
o Correlation / Regression
o Sentiment Analysis
o Word Cloud
Data visualization: 10 marks
Part C: Data analysis Report (50 marks)
Social media source and dataset attributes: 10 marks
Purpose of the analysis: 10 marks
Findings and insight: 20 marks
References, style and presentation: 10 marks
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