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Author – Ken Hobson.
When news stories or Facebook chatter turn positive, people feel safe buying and selling. When talk turns sour, listings slow. Tracking mood helps you time campaigns, pricing, and vendor advice.
How Sentiment Analysis Works in Plain English
Collect words: Grab headlines, articles, comments, and posts mentioning your suburb.
Label feelings: AI gives each sentence a score: happy, neutral, or unhappy.
Show patterns: Scores stack into charts so you see mood moving up or down.
Spot triggers: Sudden drops often follow crime reports, rate rises, or development debates.
Act early: Change messaging, release good-news stories, or hold off an auction until mood lifts.
Five-Step Workflow for Market Research
Define your patch
List suburbs, postcodes, and key landmarks you service.
Set up feeds
Add Google News, local papers, council updates, Facebook groups, Instagram hashtags, and X (Twitter) searches to one dashboard.
Run daily sentiment scoring
Use an AI tool (see below) to tag each new item as positive, neutral, or negative.
Visualise trends
Plot a simple line showing average mood for each suburb. Weekly emails keep your team informed.
Turn insight into action
Positive spike? Push just-listed ads.
Negative dip? Publish community-care content, reassure landlords, and adjust price guides if needed.
Recommended AI Tools
Tool | Quick Description |
---|---|
Talkwalker | Tracks sentiment across news, blogs, podcasts, and social media in real-time. Heatmaps and alerts show which suburbs trend positive or negative before competitors notice daily. |
Brandwatch | Aggregates millions of online mentions, then slices them by emotion, demographics, and location. Interactive timelines help compare neighbourhood reputations and spot public mood swings early. |
Google Cloud Natural Language | API scoring sentiment for any sentence in news articles, reviews, or social posts. Plug into Google News feeds to create automated suburb-level mood scoreboards nightly. |
MonkeyLearn | No-code platform for building custom sentiment classifiers. Label sample local posts once, then the model grades new content, capturing slang, sarcasm, and suburb quirks ignored. |
Meltwater | Tracks traditional media, online outlets, podcasts, and socials in one dashboard. Custom alerts highlight negative coverage, letting you prepare owner updates and proactive press responses. |
CrowdTangle | Free Meta tool surfacing high-engagement Facebook and Instagram posts for chosen suburbs. Reveals sentiment shifts and winning stories, guiding community outreach and timely comment participation. |
Turning Insights into Action
Listing presentations: Show vendors mood charts to justify pricing or marketing spend.
Content planning: Write blogs answering the week’s top worries.
Investor updates: Flag suburbs where sentiment predicts rental demand changes.
Crisis management: Respond quickly when negativity rises—issue facts before rumours spread.
Common Pitfalls and How to Avoid Them
Small sample size: Combine several sources so one angry post doesn’t skew results.
Ignoring neutral data: A swing from positive to neutral can be an early warning.
One-off checks: Schedule daily runs—sentiment shifts fast.
Blind trust in AI: Manually review outliers to catch sarcasm and local humour.
Quick-Win Checklist
List core suburbs and key search terms.
Choose a sentiment tool and connect news plus social feeds.
Automate daily scoring and a weekly PDF summary.
Share insights with sales, property management, and marketing teams.
Adjust campaigns based on trend direction every Monday.
Use this simple workflow to read the public mood like a weather report and steer your property strategies with confidence.
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Lorem ipsum
- dolor sit amet,
- consectetur adipiscing elit. Ut
- elit tellus, luctus
- nec ullamcorper mattis,
- pulvinar dapibus leo.
- Lorem ipsum
- dolor sit amet,
- consectetur adipiscing elit. Ut
- elit tellus, luctus
- nec ullamcorper mattis,
- pulvinar dapibus leo.
- Lorem ipsum
- dolor sit amet,
- consectetur adipiscing elit. Ut
- elit tellus, luctus
- nec ullamcorper mattis,
- pulvinar dapibus leo.
- Lorem ipsum
- dolor sit amet,
- consectetur adipiscing elit. Ut
- elit tellus, luctus
- nec ullamcorper mattis,
- pulvinar dapibus leo.
- Lorem ipsum
- dolor sit amet,
- consectetur adipiscing elit. Ut
- elit tellus, luctus
- nec ullamcorper mattis,
- pulvinar dapibus leo.
- Lorem ipsum
- dolor sit amet,
- consectetur adipiscing elit. Ut
- elit tellus, luctus
- nec ullamcorper mattis,
- pulvinar dapibus leo.