NMC5342 Introduction to Applied Social Media Analytics

An applied graduate course covering methods for collecting, processing, and analyzing social media data, with emphasis on computational approaches to communication research.

Instructor Zhicong Chen
Term Fall 2025
Location National University of Singapore

Course Overview

This applied graduate course equips students with the full pipeline for social media research: collecting data from APIs, analysing text and network structure, and interpreting findings in the context of communication theory. Special attention is paid to ethical and methodological rigour.

Learning Objectives

By the end of this course, students will be able to:

  • Collect social media data via REST APIs and responsible web scraping
  • Analyse linguistic patterns, sentiment, and topics in large text corpora
  • Construct and characterise social networks from interaction data
  • Apply large language models as annotation and classification aids
  • Design ethically sound social media research studies

Prerequisites

  • Intermediate Python (Introduction to Python or equivalent)
  • Familiarity with basic statistics and social science research design

Level

Graduate

Institution

Department of Communications and New Media, National University of Singapore

Key Tools and Libraries

Tool Purpose Link
PRAW Reddit API client praw.readthedocs.io
YouTube Data API YouTube data developers.google.com/youtube
spaCy NLP preprocessing spacy.io
Hugging Face Transformer models huggingface.co
NetworkX Network analysis networkx.org
Gephi Network visualisation gephi.org
BERTopic Topic modelling maartengr.github.io/BERTopic
Botometer Bot detection botometer.osome.iu.edu

Assessment

Component Weight
Weekly labs 30%
Research design memo 15%
Final project 45%
Participation 10%

Schedule

Week Date Topic Materials
1 Week 1 The Social Media Research Landscape

Affordances of social media platforms; computational communication research; big data opportunities and pitfalls.
2 Week 2 Python Refresher and Data Wrangling

Pandas DataFrames, JSON parsing, datetime handling, environment setup.
3 Week 3 Collecting Data via APIs

REST API fundamentals, authentication, rate limits, pagination; Reddit API and YouTube Data API.
4 Week 4 Web Scraping Social Media

Scraping public pages with BeautifulSoup and Playwright; legal and ethical boundaries.
5 Week 5 Descriptive Analytics: Engagement and Audience

Like/share/comment distributions, posting patterns, user growth, power-law distributions.
6 Week 6 Text Analysis of Social Media

Preprocessing tweets and posts; n-grams; TF-IDF; emoji and hashtag handling.
7 Week 7 Sentiment and Opinion Mining

VADER, transformer-based classifiers (e.g., Twitter-roBERTa), aspect-level sentiment.
8 Week 8 Topic Modeling Social Media Corpora

LDA vs. BERTopic on short text; tuning for social media noise; visualising topic change over time.
9 Week 9 Network Analysis: Structure and Diffusion

Mention, retweet, and follower networks; centrality, clustering, communities; information cascades.
10 Week 10 Misinformation and Coordinated Behaviour

Bot detection, coordinated inauthentic behaviour, echo chambers, fact-checking datasets.
11 Week 11 LLMs as Research Tools

Prompting GPT-4 / Claude for content coding, entity extraction, and synthetic annotation; validation.
12 Week 12 Ethics and Responsible Research

IRB considerations, informed consent for scraped data, anonymisation, platform ToS, GDPR basics.
13 Week 13 Final Project Presentations

Students present original social media analytics projects to the class and invited guests.