Public Sentiment Overview
View All82%
Overall
Positive Sentiment
- Very Positive42%
- Positive36%
- Neutral10%
- Negative5%
- Very Negative3%
Solutions · OSINT Intelligence
Open signals, responsibly read.
OSINT Intelligence turns public, open-source signals — news, social, forums and the public web — into aggregate narrative and issue intelligence. It is built for understanding communities in the aggregate, gathered through permitted sources, and deliberately not for covert profiling of individuals.
The line we hold
Aggregate intelligence, not surveillance
Open-source intelligence can be done responsibly or invasively, and the difference is a design decision, not a setting. Civiq.plus builds OSINT for aggregate geographic, cohort and community understanding. It does not create covert individual-level psychographic scores or hidden persuasion profiles, does not fabricate public support, and works only through permitted sources. That constraint is architectural — it shapes what the module can do, not just what it is configured to do.
- Aggregate signals, not individual tracking
- Permitted sources under each platform's terms
- Confidence and provenance on every finding
- Risk flags for human review, not automated verdicts
Citizen Feedback Trends
View All- Service Satisfaction82%↑ 8%
- Infrastructure68%↑ 5%
- Cleanliness61%↑ 4%
- Safety & Security74%↑ 6%
- Transparency79%↑ 7%
Service Delivery Monitoring
View All78%
Overall
Service Index
- On-Time Delivery81%
- Quality of Service76%
- Resolution Rate74%
- Citizen Reach79%
Functions
What it computes
Narrative clustering
Group semantically related narratives across sources and track their size, velocity and drift over time — so you see a story forming rather than a single post.
- Cross-source narrative grouping
- Velocity and drift tracking
- Geographic relevance where it can be inferred
Propagation analysis
Trace how a claim or narrative moved between channels and communities, showing origin, amplification and decay rather than just where it ended up.
- Origin and relay patterns
- Cross-media transitions
- Amplification and decay curves
Risk & misinformation flags
Surface potential false or unsupported claim clusters for human review. The platform flags for attention; it does not adjudicate truth automatically.
- Unsupported-claim clustering
- Flagged for human review
- Reversibility and risk indicators
Confidence & provenance
Every OSINT signal carries source quality, coverage and model certainty, so a thin or one-sided signal is visibly thin rather than presented as fact.
- Source-quality weighting
- Coverage and diversity scored
- Provenance on every finding
Sources
Where the signal comes from
No single source is trusted on its own. OSINT signals are calibrated against representative survey and field data, and the gap between them is itself a useful indicator.
| Source | How it is gathered | What it surfaces |
|---|---|---|
| Public social media | Posts and engagement on public accounts via permitted APIs | Aggregate topic and sentiment trends |
| News & broadcast | Print, TV, radio and digital news metadata and transcripts | Narrative pickup and cross-media spread |
| Public web & forums | Openly published pages, blogs and public discussion | Emerging issues and recurring questions |
| Search & trends | Public search-interest signals | What a community is actively looking for |
| Community channels | Signals from channels where consent and terms permit analysis | Aggregate concern clusters, labelled for representativeness |
Pipeline
From open signal to reviewed brief
- 01
Collect
Gather from permitted open sources — public APIs, news feeds, the public web — under each platform's terms.
- 02
Normalise
De-duplicate, detect language and attach a geographic unit where one can be reasonably inferred.
- 03
Cluster
Group related narratives and issues, and track how they move and grow across sources.
- 04
Score
Attach confidence and provenance so a signal's reliability is visible alongside it.
- 05
Brief
Feed the result into the twin, media briefs and the AI recommendation layer for human review.
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