Spring 2027

Social Media Analytics

Introduction to collecting and analyzing social media data to evaluate impacts on consumer choices, human interaction, and public opinion, with practical application of platform metrics.

offering recorded3 credits
Recorded instructors · Spring 2027 Kaiping Chen3.7/5

Summary

1 / 6

Past student reviews · Kaiping Chen

The workload was characterized as group-project heavy, with some students finding the material confusing.

What you’ll be able to do

  • Describe key concepts related to humans/groups/institutions’ activities on social media and ethical considerations for social media researchers

  • Select an appropriate social science qualitative or quantitative research method technique for collecting and analyzing social media data

  • Analyze and clearly communicate about the relationship between social media content and user click data

  • Demonstrate basic knowledge of the R data science software

  • Evaluate social media data’s impact on consumer choices, human interaction, and public opinion of scientific issues and industries

  • Apply metrics from social media platforms to develop strategic communication recommendations for clients, ranging from industry to policymakers

  • Analyze and synthesize relevant scholarly literature related to social media, internet studies, and computer-mediated communication

  • Formulate a research proposal articulating a primary research project studying consumer choices, human interaction, public opinion, and/or discourse on social media

Source: UW Guide

Grade history

↗
average GPA
letter grades
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AB
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All recorded terms · compare terms & instructors

Prerequisites

Course map

Satisfied Quantitative Reasoning A or graduate/professional standing

    • Satisfied Quantitative Reasoning A
    • graduate/professional standing
    take one
LSC 460

This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree
  • Any of
    • Satisfied Quantitative Reasoning A
    • graduate/professional standing

Professors

Spring 2027
Adjusted rating
RMP difficulty
captured reviews
About this rating

Raw average: 3.67/5 from 3 quality ratings. The adjusted rating blends this with the UW review average (3.66/5), weighted as 20 additional ratings. Smaller samples stay closer to that average. Each captured review is counted once in the prior; this does not correct who chooses to leave a review.

For this course: 3.0/5 raw quality · 2.0/5 difficulty · 1 reviews

RMP profile ↗ · All captured review dates; profile matched by name.

Past student reviews · Kaiping Chen

Kaiping Chen was described as passionate and friendly but occasionally unclear in her instructions. The course was group-project heavy and sometimes found to be confusing or boring, though it was recommended for students who enjoy RStudio.

Recent recorded grades — Spring 2024: 3.92 GPA, 96.7% A/AB (n=61 letter grades); Spring 2025: 3.99 GPA, 100.0% A/AB (n=77 letter grades); Spring 2026: 3.91 GPA, 96.0% A/AB (n=75 letter grades). Includes jointly taught sections.

Historical instructors & teaching patterns

KAIPING CHEN is recorded teaching in Spring 2023, Spring 2024, Spring 2025, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.

Recorded history may be incomplete and does not establish a future schedule.

Calendar & sections

Spring 2027

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction0 / 1000

Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.

Meeting source records
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Student experience

the class

Past student reviews · Kaiping Chen

Students described the course as group-project heavy, noting it could be boring or confusing at times, but recommended it for those who enjoy RStudio.

Recent recorded grades — Spring 2024: 3.92 GPA, 96.7% A/AB (n=61 letter grades); Spring 2025: 3.99 GPA, 100.0% A/AB (n=77 letter grades); Spring 2026: 3.91 GPA, 96.0% A/AB (n=75 letter grades).

difficulty & workload

Past student reviews · Kaiping Chen

The workload was characterized as group-project heavy, with some students finding the material confusing.

Past student reviews · Kaiping Chen

Kaiping Chen was perceived as passionate and friendly, though some students found her instructions and presentation style unclear at times.

Topics

  • Social media data collection and analysis
  • Impact on consumer choices, human interaction, and public opinion
  • Strategic communication recommendations using platform metrics
  • Scholarly literature in social media and internet studies

Skills

  • Selecting qualitative or quantitative research methods for social media data
  • Basic use of R data science software
  • Developing strategic communication recommendations using social media metrics
  • Formulating research proposals for social media studies

Grades

Latest available · Spring 2026— not enough history to project Spring 2027.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F

Grades over time

Through Spring 2026

More grade details Grade mix, volume & source data

Where this course fits relative to

Latest available grades · Spring 2026 · all course levels

GPA

Higher than % of other courses in this group.

Course GPAs · red marks this course’s range

letter grades

More recorded grades than % of other courses in this group.

Typical course in this group: letter grades.

About this comparison

1280 courses over the same term, each with at least 30 recorded letter grades. Cross-listed courses count once. GPA is not a measure of difficulty or teaching quality. The typical course is the median by recorded grade count; tied values are not counted as lower. Grade counts describe course scale, not unique students or typical section size.

Descriptions compare GPA with this group’s average: at least 0.20 higher or lower; otherwise close to average. Section size uses median recorded enrollment: small up to 30, mid-sized 31–99, large 100+. Lectures and discussion/lab sections are described separately.

Sources & history

UW–Madison

Catalog & offerings

Descriptions, prerequisites, and recorded course offerings.

Catalog observation history

Observations at scan time; dates do not imply when a catalog change took effect.

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Selected offering source records
LSC 460 · Spring 2027

Social Media Analytics

Recorded 2026-10-14
Raw records 
[
  {
    "run_id": "20261014T203208-0851c9a1",
    "semester": "1274",
    "observed_at": "2026-10-14 17:50:09.728220+00:00",
    "offering_id": "1274:120:026261",
    "course_id": "LSC 460",
    "course_uid": "course_270e5bf9ade902304083d7c9",
    "term_id": "1274",
    "source_course_id": "026261",
    "source_subject_id": "120",
    "title": "Social Media Analytics",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Not Applicable"
  }
]
Rate My Professors

Student reviews

Original comments behind the course and instructor summaries.

Read original reviews
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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

Explore recorded grades
Dataset & model

Recorded 2026-10-14

View the dataset on Hugging Face
Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Download part 1
Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "6ff25f4e40cafb73cde40a325fff0463f3567b3bf8a3c525c06124f8c600ce76",
  "requirements_status": "needs_review",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}