I scraped five years of posts and comments from Reddit's Adelaide subreddit.

Digging through 1.5 million of them for insights about what locals actually care about, this project asks the question:

Do approaches like this deserve a place in the community development worker's toolkit?

1.5M
posts & comments
5 yrs
2021 – 2026
90
themes discovered
8
emotions profiled

Chapter 01

Why Reddit?

IMO engaging with communities and having a yarn with locals is one of the most rewarding parts of community work.

But formal consultation can often be slow, expensive, limited in scope and — most critically — not something you can do in your pyjamas at home with a cup of tea.

Online public forums like Reddit represent the unmanaged, unsolicited community conversation: people talking to each other without an audience of practitioners in mind. r/Adelaide has over 160,000 members and five years of searchable conversation. This project gobbles it all up, runs it through a computer a few times to see if anything useful emerges.

One key limitation to acknowledge upfront is that social media platforms often skew towards a specific demographic. Users are roughly 60% male, heavily concentrated in the 18–29 age bracket, and disproportionately students, tech workers, and people who have strong opinions about mechanical keyboards. There is also a very high chance that not all of these posts were written by humans — like all online domains, these platforms are subject to the inevitable creep of AI slop.

Chapter 02

How It Works

A five-stage pipeline turns raw Reddit data into structured community intelligence.

01
Scrape
Pull five years of posts and comments from r/Adelaide via the Reddit API — 71k posts, 1.43M comments.
PRAW · Parquet
02
Preprocess
Remove bots, automod, and noise. Clean text, assign year/quarter timestamps, stratify for modelling.
pandas · regex
03
Topics
BERTopic clusters documents by semantic similarity. 50k-document sample fit, full corpus transformed in batches. Manual review labels each cluster.
BERTopic · sentence-transformers
04
Emotions
VADER sentiment and NRC Emotion Lexicon applied to every document. Eight emotions profiled per theme: anger, fear, joy, trust, anticipation, sadness, disgust, surprise.
VADER · NRCLex
05
Report
Interactive charts — volume trends, sentiment trajectories, emotion fingerprints, and thematic heatmaps — rendered per theme and over time.
Plotly · Jupyter

Chapter 03

What Adelaide
Talks About

Top 5 most discussed themes each year. Bar width = relative volume. Blue is positive, yellow is negative.

2021

2022

2023

2024

2025

What stands out

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Chapter 04

Is Adelaide a
Lonely City?

Beyond positive/negative, NRC emotion profiling reveals how a community feels about specific issues. The same volume of conversation can carry very different emotional weight.

5,422 loneliness-tagged posts and comments were extracted from r/Adelaide between 2021 and 2025. The Sankey below maps what those conversations were actually about.

Loneliness conversation on r/Adelaide spiked sharply during the Omicron wave (December 2021 – January 2022) then fell back — but has never returned to pre-pandemic baseline. Volume has slowly climbed again since 2023.

So what

Engagement doesn't have to start with a blank page. A community development worker who arrives at a consultation already knowing that housing, crime, and loneliness are the live concerns — and that gardening groups and charities are where the most positive energy sits — is better positioned to listen, and better positioned to act.