基于主题的情感分析

实验报告课程名称：数据挖掘课设实验名称：基于主题的文本情感分析实验地点：行远楼专业班级：软件1533学号：2015005677学生姓名：高聪江指导教师：王莉2017年1月1日课题代码：import pandas as pdimport jieba# from sklearn.feature_extraction.text import CountVectorizer# from sklearn.feature_extraction.text import TfidfTransformerfrom jieba import analyse# import jieba.posseg as pseg# from sklearn import feature_extractiondf = pd.read_csv('/home/jiangshen/Downloads/''数据挖掘_大数据/数据挖掘程序题/基于主题的文本情感分析/train.csv')#---------整理情感语料zongGeShu = len(df.values)qingGanCi_Train = {}for i in range(0,zongGeShu):valueMin001 = str(df.values[i][4])keyMin001 = str(df.values[i][3])preValue = valueMin001.split(sep=';')preKey = keyMin001.split(sep=';')del preKey[-1]del preValue[-1]for k in range(0,len(preKey)):dictionary = dict(zip(preKey,preValue))qingGanCi_Train = dict(qingGanCi_Train,**dictionary)#print(dictionary)print(qingGanCi_Train)df = pd.read_csv('/home/jiangshen/Downloads/''数据挖掘_大数据/数据挖掘程序题/基于主题的文本情感分析/train.csv')zongGeShu = len(df.values)#print(list(df.values[1][4]))# def quchuqingganci(str1):# stopWord = ';'# yuQieCi = list(str1)# xiangYao = []# for j in range(0,len(yuQieCi)):# if yuQieCi[j]!=stopWord:# xiangYao.append(yuQieCi[j])# return xiangYao# def quChuShuXing(str2):# stopWord = ';'# yuQie = list(str2)# print(quchuqingganci(df.values[1][3]))# for i in range(0,len(df.values)):# print(ganqingci)# print(df.values)# def ciXingPanDuan(word):# good = list# bad = list# if word in good:# return 1# if word in bad:# return -1# else:# return 0#-------------用TF-idf提取关键词# wordsList = df.values[9998][1]# vectorizer = CountVectorizer()# transformer = TfidfTransformer()# tfidf = transformer.fit_transform(vectorizer.fit_transform(wordsList)) # word = vectorizer.get_feature_names()# weight = tfidf.toarray()# print(word)# yuanzhuti = df.values[1][2]#data = '我爱你于是标有了光，水果，西瓜，哈哈，我爱水果,和橘都属于芸香科柑橘属的宽皮柑橘类，果实外皮肥厚，内藏瓤瓣# ，由汁泡和种子构成。

李时珍在《本草纲目·果部》中记载：“橘实小，其瓣味微醋（即酸），其皮薄而红，味辛而苦；柑大于橘，其瓣味酢' \# '，其皮稍厚而黄，叶辛而甘。

”一般说来，柑的果形正圆，黄赤色，皮紧纹细不易剥，多汁甘香；橘的果形扁圆，' \# '红或黄色，皮薄而光滑易剥，味微甘酸。

柑和橘虽有区别，但在日常语言中常混用，如广柑也说广橘，蜜橘也说蜜柑' \# '。

橘子中的维生素A还能够增强人体在黑暗环境中的视力和治疗夜盲症。

橘子不宜食用过量，吃太多会患有胡萝卜素' \# '血症，皮肤呈深黄色，如同黄疸一般。

若因吃太多橘子造成手掌变黄，只要停吃一段时间，就能让肤色渐渐恢复正常' \# '。

明代张岱季叔张烨芳对橘子情有独钟，据载其“性好啖橘，橘熟，堆砌床案间，无非橘者，自刊不给，'#---------------关键词提取#--------------<><><><>-------------keyWordsList = []dataList = df.values[6][1]keyWord2 = analyse.textrank(dataList,topK = 10,allowPOS=('n','v'),withFlag=True,withWeight=True) for i in range(0,zongGeShu):eachKeyWord = []dataList = df.values[i][1]keyWord2 = analyse.textrank(dataList,topK = 5,allowPOS=('n','v'),withFlag=False,withWeight=True) midList = list(keyWord2)for j in range(0,len(midList)):if midList[j][1] <1 and midList[j][1] >0.6:eachKeyWord.append(midList[j][0])keyWordsList.append(eachKeyWord)for i in range(0,zongGeShu):if len(keyWordsList[i]) == 0:keyWordsList[i] = ['']print('各个行的关键词：------------》')print(keyWordsList)#-----------情感词提取和分析-----------allGanQingCi = []allGanqingShuXing = []for i in range(0,zongGeShu):dataList = df.values[i][1]eachIdWord = []eachIdganqingci = []ciDeShuXing = []eachIdWord = jieba.lcut(dataList)for j in range(0,len(eachIdWord)):if (eachIdWord[j] in qingGanCi_Train.keys()) and (eachIdWord[j] not in eachIdganqingci):eachIdganqingci.append(eachIdWord[j])ciDeShuXing.append(qingGanCi_Train[eachIdWord[j]]) allGanQingCi.append(eachIdganqingci)allGanqingShuXing.append(ciDeShuXing)print('各个行的感情词:----------->')print(allGanQingCi)print('各个行的属性：——————————>')print(allGanqingShuXing)#测试生成结果---------》# okNum = 0# for i in range(0,zongGeShu):# keyWordstr = ';'.join(keyWordsList[i])# print(keyWordstr)# if keyWordstr==df.values[i][2]:# okNum +=1# roat = float(okNum/10000)# print('总的正确率是：',roat)#每一行的主题词：zhuTiend = []for j in range(0,zongGeShu):eachZhuTiend = []eachZhuTi = str(df.values[j][2]).split(sep=';')if len(eachZhuTi)==0:zhuTiend.append([])else:for i in range(0,len(eachZhuTi)):if (eachZhuTi[i]!='NULL'):eachZhuTiend.append(eachZhuTi[i])zhuTiend.append(eachZhuTiend)print(zhuTiend)okNum = 0for i in range(0,zongGeShu):if zhuTiend[i] == keyWordsList[i]:okNum += 1roat = float(okNum/10000)print('总的正确率是：',roat)#----------->>>将生成的数据生成CSV文件#keyWordList = []#listLen = len(dataList)#for i in range(0,listLen):# keyWord = analyse.extract_tags(dataList)#stop_key = pd.read_csv('/home/jiangshen/'#'PycharmProjects/DMshiyan/qingganfenxi/基于主题的文本情感分析/tingyongci')#print(stop_key)#print(keyWord[0],keyWord[1]) # print(dataList)# print(yuanzhuti)# print((keyWord))# print(keyWord2)# print(keyWord2[2][1])#print(df.values[0])# print(df.values[0][4])# print(df.values[9999][4][2])课题截图：。