Simple-TikTok-Post-Text-Mining

A simple case study for learning how to perform text mining on TikTok posts.
This case study uses a TikTok post discussing the Indonesian government's 50% electricity discount for June–July 2025, offered to customers using less than 1300 VA.

Original post: https://vt.tiktok.com/ZSh32YKTB/

Goals 🎯

1. Analyze user sentiment from TikTok posts (positive/negative)

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Result 📝

• TEST 1

TEST 1

Goal: Analyze sentiment on posts from [context or subset].

Sentiment analysis	Lexicon based
Accuracy	-%
Observation	-

Step by step

1. Data pre processing

   • Data cleaning
   • Word repair
   • Stemming
   • Stopword removal
   • Case folding
   • Tokenization

2. Vectorization with Term Frequency-Inverse Document Frequency (TF-IDF)

3. Sentiment analysis with lexicon-based approach

Visualization

Word Cloud Visualization from TEST 1

pie title Sentiment Analysis Pie Chart
    "Positive" : 0
    "Negative" : 0

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