tweetfeels.py 文件源码

def model_sentiment(self, b, s, fo=0.99):
        """
        Defines the real-time sentiment model given a dataframe of tweets.

        :param b: A ``TweetBin`` to calculate the new sentiment value.
        :param s: The initial Sentiment to begin calculation.
        :param fo: Fall-off factor
        """
        df = b.df.loc[b.df.sentiment != 0]  # drop rows having 0 sentiment
        newval = s.value
        if(len(df)>0):
            try:
                val = np.average(
                    df.sentiment, weights=df.followers_count+df.friends_count
                    )
            except ZeroDivisionError:
                val = 0
            newval = s.value*fo + val*(1-fo)
        return Sentiment(newval, b.influence, b.start, b.end)