1.爬虫程序
#请求爱奇艺评论接口，返回response信息
def getMovieinfo(url):
'''
请求爱奇艺评论接口，返回response信息
参数 url: 评论的url
:return: response信息
'''
session=requests.Session()
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/67.0.3396.99 Safari/537.36',
"Accept":'application/json',
"Referer":"http://m.iqiyi.com/v_19rqriflzg.html",
"Origin":"http://m.iqiyi.com",
"Host":"sns-comment.iqiyi.com",
"Connection":"keep-alive",
"Accept-Language":"zh-CN,zh;q=0.9",
"Accept-Encoding":'gzip, deflate, br'
}
# url='https://sns-comment.iqiyi.com/v3/comment/get_comments.action?agent_type=118&agent_version=9.11.5&authcookie=null&business_type=17&content_id=15068699100&hot_size=0&last_id=240947941221&page=&page_size=20&types=time&callback=jsonp_1587905939481_51622'
response=session.get(url,headers=headers)
if response.status_code==200:
return response.text
return None
#解析json数据，获取评论
def saveMovieInfoToFile(lastId,arr):
'''
解析json数据，获取评论
参数 lastId:最后一条评论ID arr:存放文本的list
:return: 新的lastId
'''
url='https://sns-comment.iqiyi.com/v3/comment/get_comments.action?agent_type=118&\
agent_version=9.11.5&business_type=17&content_id=1629256800&\
page=&page_size=10&types=time&last_id='
url+=str(lastId)
resTxt=getMovieinfo(url)
resJson=json.loads(resTxt)
comments=resJson['data']['comments']
for val in comments:
if "content" in val.keys():
arr.append(val['content'])
lastId=str(val['id'])
return lastId
2.#去除文本中特殊字符
def clear_special_char(content):
'''
正则处理特殊字符
参数 content:原文本
return: 清除后的文本
'''
s = re.sub(r"</?(.+?)>| |\t|\r", "", content)
s=re.sub(r'\n',' ',s)
s=re.sub(r'\*','\\*',s)
s=re.sub(r'[^\u4e00-\u9fa5^a-z^A-Z^0-9]','',s)
s=re.sub(r'[\001\002\003\004\005\006\007\x08\x09\x0a\x0b\x0c\x0d\x0e\x0f'\
'\x10\x11\x12\x13\x14\x15\x16\x17x18\x19\x1a\x1b\x1c\x1d\x1e\x1f'\
'\x20\x21\x22\x23\x24\x25\x26\x27\x28\x29\x2a\x2b\x2c\x2d\x2e\x2f'\
'\x30\x31\x32\x33\x34\x35\x36\x37\x38\x39\x3a\x3b\x3c\x3d\x3e\x3f]','',s)
s=re.sub(r'[a-zA-Z]','',s)
s=re.sub('^d+(\.\d+)?$','',s)
return s
3.分词
def fenci(text):
'''
利用jieba进行分词
参数 text:需要分词的句子或文本
return：分词结果
'''
jieba.load_userdict("words.txt")
# import pdb; pdb.set_trace()
seq=jieba.lcut(text,cut_all=False)
return seq
4.停止词
def stopwordslist(file_path):
'''
创建停用词表
参数 file_path:停用词文本路径
return：停用词list
'''
stopwords=[line.strip() for line in open(file_path,encoding='utf-8').readlines()]
return stopwords
5.去停止词
def movestopwords(sentense,stopwords,counts):
'''
去除停用词,统计词频
参数 file_path:停用词文本路径 stopwords:停用词list counts: 词频统计结果
return：None
'''
out=[]
for word in sentense:
if word not in stopwords:
if len(word)!=1:
counts[word]=counts.get(word,0)+1
return None
6.绘制词频统计表
def drawcounts(counts,num):
'''
绘制词频统计表
参数 counts: 词频统计结果 num:绘制topN
return：none
'''
x_aixs=[]
y_aixs=[]
c_order=sorted(counts.items(),key=lambda x:x[1],reverse=True)
for c in c_order[:num]:
x_aixs.append(c[0])
y_aixs.append(c[1])
matplotlib.rcParams['font.sans-serif'] = ['SimHei'] # 指定默认字体
# matplotlib.rcParams['axes.unicode_minus'] = False
plt.bar(x_aixs,y_aixs)
plt.title("词频统计结果")
plt.show()
return
7.根据词频绘制词云图
def drawcloud(word_f):
'''
根据词频绘制词云图
参数 word_f:统计出的词频结果
return：none
'''
cloud_mask=np.array(Image.open("/home/aistudio/ai.png"))
st=set(['东西',"这是"])
wc=WordCloud(background_color="white",
mask=cloud_mask,
max_words=150,
font_path="/home/aistudio/simsun.ttc",
min_font_size=10,
max_font_size=100,
width=400,
relative_scaling=0.3,
stopwords=st
)
wc.fit_words(word_f)
wc.to_file('pic.png')
8.使用hub对评论进行内容分析
def text_detection(text,file_path):
'''
使用hub对评论进行内容分析
return：分析结果
'''
pdlstm=hub.Module(name='porn_detection_lstm')
test_text=[]
f = open("aqy.txt",'r',encoding='utf-8')
for line in f:
if len(line.strip())==1:
continue
test_text.append(line)
f.close()
input_dict={"text":test_text}
results=pdlstm.detection(data=input_dict,use_gpu=True,batch_size=1)
for index,item in enumerate(results):
if item['porn_detection_key']=='porn':
print(item['text'],':',item['porn_probs'])
9.
#评论是多分页的，得多次请求爱奇艺的评论接口才能获取多页评论,有些评论含有表情、特殊字符之类的
#num 是页数，一页10条评论，假如爬取1000条评论，设置num=100
if __name__ == "__main__":
num=110
lastId='0'
arr=[]
with open('aqy.txt','a',encoding='utf-8') as f:
for i in range(num):
lastId=saveMovieInfoToFile(lastId,arr)
time.sleep(0.5)
for item in arr:
Item=clear_special_char(item)
try:
f.write(Item+'\n')
except Exception as e:
print(Item)
print('含有特殊字符')
print("共爬取评论:",len(arr))
10.对爬取的数据分词，去停止词
f =open('aqy.txt','r',encoding='utf-8')
counts={}
for line in f:
if line.strip():
words=fenci(line)
# print(words)
# import pdb; pdb.set_trace()
stopwords=stopwordslist("stopwords.txt")
movestopwords(words,stopwords,counts)
f.close()
11.绘制词频统计表
drawcounts(counts,10)
12.绘制词云
drawcloud(counts)
13.使用hub对评论进行内容分析
file_path='aqy.txt'
test_text=[]
text_detection(test_text,file_path)
14.显示生成的词云图像
display(Image.open('pic.png')) #显示生成的词云图像
