A toolkit to extract opinions and useful information from text
pip install opinionx - Find opinions
from opinionx.text import get_opinion text=open("test.txt",'r',encoding='utf-8').read() opinion_words=['表示','认为','说','介绍','提出','透露','指出','强调','：'] list_opinion,_,_=get_opinion(text,lang='zh',opinion_words=opinion_words) for opinion in list_opinion: print(opinion)- Find Leader's Opinions
from opinionx.text import get_leader_opinions text=open("test.txt",'r',encoding='utf-8').read() list_opinion = get_leader_opinions(text,save_path="", search_keywords_path="data/search_keywords.csv",leader_path="data/g20_leaders.csv") print() for opinion in list_opinion: print(opinion) print(opinion["opinion"]) print(opinion["first_found_keyword"]) print(opinion["first_found_leader"]) print()- run tf-idf and tf models for massive text files
from opinionx.tfidf_shell import * run_tfidf_shell(input_folder="tfidf_folder/raw_data", # a list of text files output_folder="tfidf_folder/output", # output folder user_dict_path="tfidf_folder/user_dictionaries", # the folder contains csv files with each line as a word font_path="utils/fonts/SimHei.ttf",# use it when analysis Chinese text is_html=True )The opinionx project is provided by Donghua Chen.