基于BosonNLP情感分析

科技前沿 • 2025-01-25 11:37 • 阅读 37
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# -*- coding:utf-8 -*- import pandas as pd import jieba #基于波森情感词典计算情感值 def getscore(text): df = pd.read_table(r"BosonNLP_dict\BosonNLP_sentiment_score.txt", sep=" ", names=['key', 'score']) key = df['key'].values.tolist() score = df['score'].values.tolist() # jieba分词 segs = jieba.lcut(text,cut_all = False) #返回list # 计算得分 score_list = [score[key.index(x)] for x in segs if(x in key)] return sum(score_list) #读取文件 def read_txt(filename): with open(filename,'r',encoding='utf-8')as f: txt = f.read() return txt #写入文件 def write_data(filename,data): with open(filename,'a',encoding='utf-8')as f: f.write(data) if __name__=='__main__': text = read_txt('test_data\微博.txt') lists = text.split('\n') # al_senti = ['无','积极','消极','消极','中性','消极','积极','消极','积极','积极','积极', # '无','积极','积极','中性','积极','消极','积极','消极','积极','消极','积极', # '无','中性','消极','中性','消极','积极','消极','消极','消极','消极','积极' # ] al_senti = read_txt(r'test_data\人工情感标注.txt').split('\n') i = 0 for list in lists: if list != '': # print(list) sentiments = round(getscore(list),2) #情感值为正数，表示积极；为负数表示消极 print(list) print("情感值：",sentiments) print('人工标注情感倾向：'+al_senti[i]) if sentiments > 0: print("机器标注情感倾向：积极\n") s = "机器判断情感倾向：积极\n" else: print('机器标注情感倾向：消极\n') s = "机器判断情感倾向：消极"+'\n' sentiment = '情感值：'+str(sentiments)+'\n' al_sentiment= '人工标注情感倾向:'+al_senti[i]+'\n' #文件写入 filename = 'result_data\BosonNLP情感分析结果.txt' write_data(filename,'情感分析文本：') write_data(filename,list+'\n') #写入待处理文本 write_data(filename,sentiment) #写入情感值 write_data(filename,al_sentiment) #写入机器判断情感倾向 write_data(filename,s+'\n') #写入人工标注情感 i = i+1
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基于BosonNLP情感分析

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