ENGINE / 02
Reading the mood of a nation in three languages.
Trilingual NLP across Tamil, Sinhala, and English social streams, mapped to district-level political heat in near real time.
Corpus
Tamil · Sinhala · English
Trilingual Data Ingestion
- Social media firehose: Twitter/X, Facebook, TikTok, YouTube comments
- News article scraping across 40+ Sri Lankan publications
- WhatsApp and Telegram public-channel monitoring (anonymised)
- Forum and blog sentiment from diaspora communities
NLP Engine
Custom fine-tuned models
Language Understanding
- Transformer-based sentiment classifiers fine-tuned on Sri Lankan political discourse
- Named entity recognition for politicians, parties, policies, and regions
- Code-switching detection: seamless handling of Tamil-English and Sinhala-English mixed text
- Sarcasm and irony detection calibrated to South Asian rhetorical patterns
Geo-Mapping
Real-time spatial overlay
District-Level Heat Maps
- Geotagged content mapped to 160+ administrative districts
- Sentiment velocity: rate of change in public opinion by region
- Topic clustering: which issues dominate which districts
- Anomaly detection: sudden sentiment spikes flagged for campaign response
Delivery
Dashboard + alerts
Operator Interface
- Live dashboard with filterable sentiment timelines by region, language, topic
- Automated daily briefings for campaign strategists
- Push alerts on sentiment breakpoints (threshold-triggered)
- Exportable reports for coalition meetings and press strategy