使用SO-PMI算法生成经济领域情感词典
使用SO-PMI(情感倾向点互信息算法)算法生成特定领域情感词典（本项目以经济类文本为例）
若对您有用，请star一下，谢谢！
python PMI.py
1）输入：
六十几万个文档，每个文档为一行，保存在'./data/corpus.txt'中，由于语料库太大所以只保留少部分文本
种子情感词：正负情感词共190个，格式为 ‘词 极性’，保存在'./data/sentiment_words.txt'中
2）输出：
生成正向情感候选词，保存在'./data/pos.txt'中
生成负向情感候选词，保存在'./data/neg.txt'中
1、本算法效果受训练语料影响，语料越大，效果越好
2、本算法效率受训练语料影响，语料越大，训练越耗时190个种子词，六十几万条的语料，大约耗时六百多秒
3、候选词的选择，主要还是靠人工效果会比较好
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