Tendie.bot Sentiment Intelligence Methodology

Tendie.bot measures the mood of retail investors on Reddit — in real time.
By analyzing millions of posts and comments across major finance communities, we transform unstructured discussions into reliable, data-backed insights about how traders actually feel.

Most platforms that “track sentiment” only count mentions of tickers.
Tendie.bot goes further: it understands context, filters noise, and uses AI to distinguish between hype, sarcasm, and genuine market conviction.
The result is cleaner, smarter data you can trust.

How We Collect Data

Tendie.bot continuously monitors major investing subreddits including r/wallstreetbets, r/stocks, r/options, r/investing, and r/pennystocks.
Every post and comment is collected through Reddit’s API along with details such as author, subreddit, engagement, and timestamp.

This complete record allows Tendie.bot to track market sentiment with precision — filtering by timeframe, source, or even user — while maintaining full transparency and auditability.
No scraped screenshots or approximations, just structured, verifiable data.

How We Identify Stocks and Tickers

Our proprietary ticker extraction engine automatically identifies companies and assets mentioned in Reddit conversations.
It doesn’t just look for dollar signs or all-caps words. It reads the context.

The system recognizes a wide variety of formats — $TSLA, TSLA, “Tesla,” or even phrases like “Elon’s company.”
Each candidate is validated against a live database of stocks, ETFs, and cryptocurrencies to eliminate false matches.
It also uses fuzzy matching to interpret slang or informal references (e.g. “nvda gang,” “apple bags”).

This multi-layered process ensures that every mention is meaningful, reducing noise and delivering accurate volume and sentiment counts across symbols.

How We Understand Sentiment

Once tickers are identified, Tendie.bot’s natural language analysis engine goes to work.
Each Reddit post is reviewed by an AI model that determines whether it reflects a genuine investment opinion — and whether that opinion is bullish, bearish, or neutral.

Instead of guessing from keywords like “buy” or “sell,” our model reads the entire post, factoring in tone, intent, and supporting reasoning.
Each post is assigned a confidence score and a concise explanation that makes results transparent and auditable.

This process converts messy human conversation into structured data points suitable for time-series analysis, dashboards, and predictive models.

Data Quality and Reliability

Tendie.bot’s sentiment database is built for integrity.
Spam accounts and known bots are automatically excluded.
Posts are deduplicated, validated, and stored with timestamps so that trends remain consistent over time.
Every AI-generated analysis follows a strict schema to prevent incomplete or malformed entries.

The result is a clean, queryable dataset that reflects real investor discussions — not noise, reposts, or speculation amplified by bots.

How We Compare

Platforms like ApeWisdom and SwaggyStocks helped introduce the idea of tracking retail investor sentiment — but they rely on shallow parsing that misses the bigger picture.

• ApeWisdom focuses on counting how many times a ticker is mentioned across a few subreddits. It doesn’t analyze context or tone, so sarcasm, spam, and casual references all count the same.
• SwaggyStocks adds basic keyword tagging (like “calls” or “puts”) to suggest sentiment direction, but it’s still rule-based and often misclassifies posts that mix humor or irony with genuine opinions.

Tendie.bot moves beyond these limitations.
We use verified ticker extraction, natural language understanding, and AI reasoning to measure why a post is bullish or bearish — not just that it mentions a ticker.
Every data point is backed by the original post and can be traced, audited, and reanalyzed as models improve.

Ongoing Refinement and Model Improvement

Tendie.bot is still in its early stages.
While our current pipeline delivers structured, trustworthy sentiment data, we recognize that human language — especially on Reddit — is full of nuance, humor, and sarcasm that even advanced models can misinterpret.

We’re continuously refining our detection algorithms, retraining AI models with new data, and incorporating user feedback to reduce false positives and improve contextual accuracy.
Each iteration brings us closer to a system that not only captures what traders say but truly understands what they mean.

Why It Matters

Retail sentiment influences short-term price action and liquidity — but only if measured accurately.
Tendie.bot was built to separate real conviction from noise, giving traders, analysts, and researchers a dependable signal grounded in transparent, explainable data.