No usable source links are available for this idea. Its signal notes and scores need independent verification.
University administration and Ministry of Education officials driving university restructuring spend 5–8 hours per week manually monitoring merger-related sentiment across faculty councils, student associations, alumni groups, and regional media. Failure to detect opposition sentiment early frequently delays merger timelines by 6 months to 1 year.
Real-time crawling of news, social media, and online communities based on university names and merger keywords, combined with sentiment analysis (for/against/neutral) dashboard and early-warning issue alerts — enabling decision-makers to track public opinion in real time and formulate response strategies.
| N Novelty | 1-5 | How uncommon the service is in market context. |
| U Urgency | 1-5 | How urgently users need this problem solved now. |
| M Market | 1-5 | Market size and growth potential from proxy indicators. |
| R Realizability | 1-5 | Buildability for a small team with realistic constraints. |
| V Validation | 1-5 | Validation signal quality from competition and demand data. |
| Tech Complexity | / 40 | Difficulty of core implementation stack. |
| Data Availability | / 25 | Practical availability and cost of required data. |
| MVP Timeline | / 20 | Expected time to ship a usable MVP. |
| API Bonus | / 15 | Bonus for viable public API leverage. |
| Competition | / 20 | Signal quality from competitor landscape. |
| Market Demand | / 20 | Demand proxies from search and mention patterns. |
| Timing | / 20 | Fit with current shifts in tech, behavior, and regulation. |
| Revenue Signals | / 15 | Reference evidence for monetization viability. |
| Pick-Axe Fit | / 15 | How well the concept serves participants in a trend. |
| Solo Buildability | / 10 | Practicality for lean-team implementation. |