Welcome to MSMK7025: Algorithms, Big Data and Online Marketplaces!

Class A: Wed & Sat 2:00pm - 5:00pm (ATC B2)
Class B: Wed & Sat 6:30pm - 9:30pm (ATC B2)
Class Days: Dec 8, 11, 15, 18, 22; Jan 5, 8, 12, 15, 19.
Final Exam: Jan 26 (Wednesday).

Instructor: Xi Li

• You can download the software for the course here: R, R Studio and Tableau Public
• Note: When installing R/Rstudio, make sure your path does not contain any non-english characters. (安装路径必须为纯英文，否则运行会出错)
• No textbooks for the course.

Grading:
10%: Group Paper Presentation (~12 minutes, in class). Details Spreadsheet Class A Class B
30%: Two Group Data Projects

• For details, please see the slides for the data workshops
• Deadline for Project I: Dec 29, 5pm (Class A) 9:30pm (Class B)
• Deadline for Project II: Jan 22, 5pm (Class A) 9:30pm (Class B)

10%: In-class Participation
50%: Final Exam (Multiple Choice Only; Open-book Open-notes)
Sample questions for the final exam will be released in the last session (i.e., Jan 19).

Lecture 1: Introduction

Slides (No Answer Keys) Slides (With Answer Keys)

Lecture 2: Data analysis: An R approach

This class introduces some basic R operations. The lecture is designed for students with zero background in computer programming/R. We will explore how to use R to conduct simple data analysis.
Note: Please get R installed on your laptop and bring it with you.
Slides
Teaching materials: A beginner’s guide to R
Troubleshooting for package installation: Here

Lecture 3: Beyond Linear Regression (Rescheduled)

Note: Please get R installed on your laptop and bring it with you.
Slides (No Anwer Keys) Slides (With Anwer Keys)

Lecture 4: Data Workshop I (Rescheduled)

Note: Please get R installed on your laptop and bring it with you.
Slides
Dataset: CSV
Sample Data Analysis with R: Sample

Lecture 5: Data visualization: A Tableau approach (Rescheduled)

This class introduces Tableau Public, a power data visualization software. It is simple and you will have fun using it.
Note: Please get Tableau Public installed on your laptop and bring it with you.
Slides
Data files: Superstore Data, Movie Data Tableau Public Gallery
Example of Word Cloud: Word Cloud Tagul for generating Word Cloud: Tagul
Dituhui for creating a map for China

Lecture 6: Data Scraping

Note: Please get R and Chrome browser installed on your laptop and bring it with you.
Slides
Teaching materials: Scraper (HKU), Scaper (Marketing Science Journal), Scraper (MIT), Scraper (Photo)

Lecture 7: Causality

Slides
Optional reading: a discussion of some famous instruments (in simplified Chinese) here
Optional reading: the 2021 Nobel Prize in Economics here for a simplified Chinese version, and here for an English version.

Lecture 8: Text Analysis

Note: Please get R installed on your laptop and bring it with you.
Slides
Codes: text analysis, topic models
A Chinese sentiment lexicon here
Demonstration of sentiment analysis.
Demonstration of LDA. Data files: document and stopword

Lecture 9: Data Workshop II

Note: Please get R installed on your laptop and bring it with you.
Slides
Teaching materials: Quadratic Regression, Interactions and Fixed Effects
Dataset: XLSX, CSV

Note: In the previous dataset, some values were mistakenly treated as strings. The CSV file is now updated, and you can continue using it. We thank the students for pointing this out and apologize for the inconvenience.

Sample Data Analysis with R: Sample

Lecture X: Recommender Systems and Final Review (Online Class)

Note: Due to the university policy, the class will be delivered online exclusively. Please join the class through ZOOM. We will also conduct a brief review of the class with sample questions for final.
ZOOM Link: Class A, Class B
Slides
Final Review
Thanks for taking the course! Finally, the intructor would invite you to conduct an anonymous survey to gather your feedback: Link