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A sentiment analysis package used for traditional Chinese.

Project description

senti_c (sentiment analysis toolkit for traditional Chinese)

簡介

本工具為繁體中文情感分析套件,支援三種類型分析:句子情感分類、屬性術語提取、屬性情感分類;同時提供函數供使用者應用其它資料重新微調模型。

目錄


執行環境

  • python3.7

安裝方式

  1. pip
pip install senti_c 
  1. from source
git clone https://github.com/julielanblue/senti_c
cd senti_c
python3 setup.py install

功能介紹

  1. 句子情感分類:預測
from senti_c import SentenceSentimentClassification

sentence_classifier = SentenceSentimentClassification()

test_data = ["我很喜歡這家店!超級無敵棒!","這個服務生很不親切..."]  
result = sentence_classifier.predict(test_data,run_split=True,aggregate_strategy=False)  # 可依據需求調整參數
  • 結果如下:

Sample

  1. 句子情感分類:重新微調模型
from senti_c import SentenceSentimentModel

sentence_classifier = SentenceSentimentModel()
sentence_classifier.train(data_dir="./data/sentence_data",output_dir="test_fine_tuning_sent")  # 可依據需求調整參數
  1. 屬性情感分析:預測
from senti_c import AspectSentimentAnalysis

aspect_classifier = AspectSentimentAnalysis()

test_data = ["我很喜歡這家店!超級無敵棒!","這個服務生很不親切..."]   
result = aspect_classifier.predict(test_data,output_result="all")  # 可依據需求調整參數
  • 結果如下:

Sample

Sample

Sample

Sample

  1. 屬性情感分析:重新微調模型
from senti_c import AspectSentimentModel

aspect_classifier = AspectSentimentModel()
aspect_classifier.train(data_dir="./data/aspect_data",output_dir="test_fine_tuning_aspect")  # 可依據需求調整參數

範例程式

相關功能demo可參考examples資料夾中的jupyer lab檔案。

資料

本研究蒐集Google評論上餐廳與飯店領域評論內容、並進行句子情感分類、屬性情感分析標記 (屬性標記與情感標記)。

相關資料格式請見data資料夾。

引用

引用請註記來源:NTU BAEIR lab

致謝

本套件基於 Hugging Face 團隊開源的 transformers

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