Vítor
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PROJECT 11 / 2026Technical experiment

Access Sentiment

Comments stop being noise once they become a decision queue.

NLP · Data product
MY ROLE

Data · Development · Interface

CONTEXT

Personal project

TECHNOLOGIES
  • Python
  • Streamlit
  • YouTube API
EXPLORE
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Illustrative concept of the Access Sentiment analysis dashboard
ACCESS SENTIMENT / ANALYTICSILLUSTRATIVE CONCEPT

An end-to-end NLP experiment, from a synthetic dataset to an analysis dashboard and YouTube comment classification.

The challenge

Show the full cycle of a data product without hiding the limits of a synthetic dataset and an experimental model.

The response

The project combines data generation, preprocessing, training, model comparison, a seven-page dashboard and integration with the YouTube API.

01

Present the solution as a pipeline experiment, not a market-ready model.

02

Prioritize an interface that drives action, such as the critical comments queue.

03

Treat API failures and missing credentials as product states.

04

Read perfect metrics on synthetic data as a methodological warning.

03 / CURRENT STAGEEVIDENCE & NEXT STEPS

What exists today.

Dashboard

7 pages

Overview, channels, topics, queue, word clouds and YouTube

Dataset

1,000

Labeled synthetic comments

Models

2

Logistic regression and Naive Bayes

NEXT MOVE

Add a real annotated dataset, a baseline, error analysis and a reproducible public demo.

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KEEP EXPLORING / 12

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