Social Media Analytics
National Technical Research Organisation (NTRO) · Miscellaneous · Software
The analytics are fine but the framework hinges on live X and Telegram ingestion that platform restrictions now make the hardest part — anchor on Telegram, be honest about X access, and treat demographic inference cautiously rather than as a confident output.
What it actually is
Understanding an online community means knowing how people feel, who they are, what topics grip them, and how influence spreads between them. The ask is a framework that ingests social media data across platforms and simultaneously infers sentiment, maps demographics, tracks trending narratives and performs network analysis to reveal how information flows.
What to build
A multi-platform analytics framework with a time-stamped ingestion pipeline pulling posts and interactions — mandatorily from X and Telegram, ideally Instagram and Facebook, optionally Reddit or YouTube comments — feeding four analysis vectors: nuanced sentiment and emotion detection including sarcasm and stance mapped along a timeline, demographic inference of the audience, automated trend and narrative tracking, and link and network analysis identifying influencers and how information propagates through the follower graph, presented on a dashboard that shows all four dimensions against the conversation chronology.
Smallest thing that wins the room
Ingest a timeline of posts around a topic and show sentiment shifting over the chronology, the top trending narratives surfacing, and the network graph highlighting the handful of accounts through which the narrative actually propagated.
How crowded this one gets
A guess, projected from the 2025 statements — the last year where both the submission counts and the winners were published.
Quieter than 38% of the 226 · #140 of 226 by expected field
A normal-sized field. Your idea has to be good, not miraculous.
Why: defence, intelligence and space bodies drew small fields.
This is a guess, not a fact
Nobody has published 2026’s numbers yet. This is an analysed estimate from last year’s pattern, so please do not take it as the truth — check the live counter on the SIH portal before you decide anything. The range covers the middle half of likely outcomes, so one statement in two lands outside it. Entry closes at 500 ideas per statement, so no range goes past that — a statement that reaches the cap fills and shuts rather than drawing an unlimited crowd. The model reads only three things a team can see before choosing — software or hardware, the theme, and what kind of body posted it — and those explain about a quarter of the variation in last year’s field sizes (R² 0.25 on held-out statements). Trust the band more than the number, and the ordering more than either. It cannot see how good your idea is, which is the part that actually decides it.
The scores
The number is the shorthand. The line under it is the reason.
Acceptance potential
3/5The analysis is genuinely useful and the network-propagation angle is compelling, but the mandated live ingestion from X and Telegram is a data-access wall that undermines the framework's premise, and demographic inference from social profiles is both unreliable and ethically fraught.
Feasibility
2/5The analysis techniques are all standard, but the description mandates live ingestion from X and Telegram, and X's API is now heavily paywalled while platform anti-scraping actively blocks collection — so the data acquisition the whole framework depends on is the real and severe obstacle, not the analytics.
Innovation scope
3/5The four analysis vectors are named and each is an established technique, so your room is in combining them coherently along a timeline and in demographic inference, rather than in the individual analyses.
Clarity
3/5The five components are enumerated with platform priorities, but the framing is broad — four different analytical disciplines bundled together — so a team knows the breadth without knowing which vector is actually the priority.
Effort
MassiveA multi-platform ingestion pipeline plus sentiment, demographics, trend tracking and network analysis is five substantial components spanning data engineering and four analysis disciplines.
Demo-ability
MediumThe sentiment-timeline and propagation graph demo well on a prepared dataset, but the framework's value rests on live multi-platform ingestion that you likely cannot show working against the real APIs.
In its favour
- Green flag: Telegram has an accessible API and public channels, so it is the most demonstrable of the required platforms and a good anchor for the build
- Green flag: Narrative propagation through a network graph is a striking, high-value visual that speaks directly to NTRO's interests
- Green flag: Each analysis vector rests on established techniques, so the risk is data access rather than algorithmic
- Green flag: Academic social datasets can substitute for live ingestion to prove the analytics while you handle live data separately
Against it
- Red flag: X's API is now expensive and its anti-scraping is aggressive, so live ingestion from a mandated platform is the framework's biggest risk and it is outside your control
- Red flag: Demographic inference from social profiles is unreliable and raises real privacy and bias concerns, so treating it as a confident output is both technically and ethically shaky
- Red flag: Bundling four analytical disciplines invites four shallow implementations rather than one strong one
- Red flag: Sarcasm and nuanced-emotion detection is genuinely unsolved, so promising it and demoing a basic three-class sentiment model under-delivers on the stated requirement
What you will be writing
- X API v2 / Telegram API ingestion
- Transformer sentiment + stance/sarcasm detection
- BERTopic trend and narrative tracking
- NetworkX / Gephi influence and propagation analysis
- Demographic inference (with caveats)
- Time-series dashboard (Streamlit / React)
- Social media intelligence
- Network analysis
- Sentiment analysis
Prior art to read before you start
multi-vector social media analytics · narrative propagation and influence mapping · timeline sentiment tracking
Analysed by Claude Opus. Every score above is a judgment call with its reasoning attached — kindly cross-check this against the official statement on the SIH portal before your team commits to it.