Tweepy 跟踪多个术语 [英] Tweepy Tracking Multiple Terms

问题描述

我正在对推文进行内容分析.我正在使用 tweepy 返回匹配某些术语的推文，然后将 N 条推文写入 CSV 文件以进行分析.创建文件和获取数据不是问题，但我想减少数据收集时间.目前我正在遍历文件中的术语列表.一旦达到 N(例如 500 条推文)，它就会移动到下一个过滤器项.

我想将我的所有术语(少于 400 个)输入到一个变量中，并且所有结果都匹配.这也有效.我无法得到的是来自 Twitter 的关于状态中匹配的术语的返回值.

class CustomStreamListener(tweepy.StreamListener):def __init__(self, output_file, api=None):super(CustomStreamListener, self).__init__()self.num_tweets = 0self.output_file = output_filedef on_status(self, status):清洁 = status.text.replace('\'','').replace('&amp;','').replace('>','').replace(',','').replace("\n",'')self.num_tweets = self.num_tweets + 1如果 self.num_tweets <500:self.output_file.write(topicName + ',' + status.user.location.encode("UTF-8") + ',' +cleaned.encode("UTF-8") + "\n")打印(捕获推文编号"+ str(self.num_tweets)+搜索词:+主题名称)返回真别的:返回错误sys.exit("终止")def on_error(self, status_code):打印 >>sys.stderr, '遇到状态码错误:', status_codereturn True # 不要杀死流def on_timeout(self):打印 >>sys.stderr, '超时...'return True #不要杀死流with open('termList.txt', 'r') as f:主题 = [line.strip() for line in f]对于主题中的主题名称:戳 = datetime.datetime.now().strftime(topicName + '-%Y-%m-%d-%H%M%S')以 open(stamp + '.csv', 'w+') 作为 topicFile:sapi = tweepy.streaming.Stream(auth, CustomStreamListener(topicFile))sapi.filter(track=[topicName])

特别是我的问题是这个.如果 track 变量有多个条目，我如何获得匹配的内容?我还将声明我对 python 和 tweepy 比较陌生.

预先感谢您的任何建议和帮助！

解决方案

您可以根据匹配的术语检查推文文本.类似的东西:

<预><代码>>>>a = "你好，这是一条推文">>>条款 = [这个"]>>>匹配 = []>>>对于 i，枚举中的术语(术语):...如果(a中的术语):...matches.append(i)...>>>火柴[0]>>>

这将为您提供与该特定推文 a 匹配的所有术语.在这种情况下，这只是这个"术语.

I am doing content analysis on tweets. I'm using tweepy to return tweets that match certain terms and then writing N amount of tweets to a CSv file for analysis. Creating the files and getting data is not an issue, but I would like to reduce data collection time. Currently I am iterating through a list of terms from a file. Once the N is reached (eg 500 tweets), it moves to the next filter term.

I would like to input all my terms (less than 400) into a single variable and all the results to match. This works too. What I cannot get is a return value from twitter on what term matched in the status.

class CustomStreamListener(tweepy.StreamListener):
    def __init__(self, output_file, api=None):
        super(CustomStreamListener, self).__init__()
        self.num_tweets = 0
        self.output_file = output_file

    def on_status(self, status):
       cleaned = status.text.replace('\'','').replace('&','').replace('>','').replace(',','').replace("\n",'')
        self.num_tweets = self.num_tweets + 1
        if self.num_tweets < 500:
            self.output_file.write(topicName + ',' + status.user.location.encode("UTF-8") + ',' + cleaned.encode("UTF-8") + "\n")
            print ("capturing tweet number " + str(self.num_tweets) + " for search term: " + topicName)
            return True
        else:
            return False
            sys.exit("terminating")

    def on_error(self, status_code):
        print >> sys.stderr, 'Encountered error with status code:', status_code
        return True # Don't kill the stream

    def on_timeout(self):
        print >> sys.stderr, 'Timeout...'
        return True #Don't kill the stream

with open('termList.txt', 'r') as f:
  topics = [line.strip() for line in f]

for topicName in topics:
    stamp = datetime.datetime.now().strftime(topicName + '-%Y-%m-%d-%H%M%S')
    with open(stamp + '.csv', 'w+') as topicFile:
        sapi = tweepy.streaming.Stream(auth, CustomStreamListener(topicFile))
        sapi.filter(track=[topicName])

Specifically my issue is this. How do I get what matched if the track variable has multiple entries? I will also state that I am relatively new to python and tweepy.

Thanks in advance for any advice and assistance!

解决方案

You could check the tweet text against your matching terms. Something like:

>>> a = "hello this is a tweet"
>>> terms = [ "this "]
>>> matches = []
>>> for i, term in enumerate( terms ):
...     if( term in a ):
...             matches.append( i )
... 
>>> matches
[0]
>>> 

Which would give you all of the terms that that specific tweet, a, matched. Which in this case was just the "this" term.

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