基于词典的社交媒体内容的情感分析（Python实现）

import time import jieba emotion_dic = {} filename = 'BosonNLP_sentiment_score.txt' # txt文件和当前脚本在同一目录下，所以不用写具体路径 with open(filename, 'rb') as file: while True: try: senList = file.readline().decode('utf-8') # print(senList) senList = senList[:-1] senList = senList.split(' ') emotion_dic[senList[0]] = senList[1] except IndexError: break def get_emotion(score): emotion_archive = ['绝望，十分愤怒，对生活不在抱有希望', '难过，失望，抑郁', '有点小难过或者小愤怒', '轻微的难受或者不屑，想得太多啦，洗洗睡觉吧', '生活也就这样吧', '有点小开心或者小激动', '蛮开心的，生活多美好', '喜笑颜开，每天的太阳都是新的，生活充满了希望'] if score <= -3.9: return emotion_archive[0] elif -3.9 < score <= -2.5: return emotion_archive[1] elif -2.5 < score <= -1: return emotion_archive[2] elif -1 < score <= 0: return emotion_archive[3] elif 0