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SmrfHdl/Text-Sentiment-Analysis-With-Spark

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This repository contains a project for performing text sentiment analysis using Apache Spark and the BERT (Bidirectional Encoder Representations from Transformers) model. The goal is to efficiently analyze large volumes of text data and accurately classify sentiments, leveraging the scalability of Spark and the advanced capabilities of BERT.

active 2024-12-07 → 2024-12-07 (UTC)

Complete coverage27,946 / 27,946 hourly files (100%) · 2 absent upstream2023-08-15 → 2026-10-22 (UTC)
Events
6
Pushes
4
Pull requests
0
Issues
0
Stars
0
Forks
0

Activity over time

Daily event counts in the loaded window

Line chart, 1 days from 2024-12-07 to 2024-12-07. Pushes: 4 total, peak 4 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.

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  • Pull requests
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  • Comments
  • Stars

Top contributors

Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity

ContributorContributionsPushesPRsComments
SmrfHdl4400

Recent activity

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No issue or PR events — this repo's activity is pushes only.

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.