使用NLP库textblob进行情感分析-红楼梦评论_textblob情感评分

最近做了一个分析国外读者对红楼梦评价的小项目。这部分是使用textblob库对评论进行情感分析，得到情感值，并且进行分类，生成词云。
生成直方图、条形图的数据分析过程见我的这篇文章

读入的数据是这样的格式。包含两行，一行评论，一行url来源。

生成的结果是这样的result.csv文件

词云图片：

代码如下

from textblob import TextBlob
from wordcloud import WordCloud
import pandas as pd
import numpy as np
import csv
from os import listdir

def getComments(filename): # 获取评论列表、评论中所有的单词，以空格分隔
    comments = np.zeros(0)
    words = ''
    com_file = pd.read_csv(filename)
    comments = np.append(comments, com_file['comment'])
    for each in comments:
        words += each
    replace_list = [',', '.', '\'', '\"']
    for each in replace_list:
        words = words.replace(each, ' ')
    return comments, words

def getWordCloud(text_str, picture_name): # 生成词云
    wordcloud = WordCloud(background_color="white",width=1980, height=1080, margin=2, random_state=0).generate(text_str)
    wordcloud.to_file(picture_name)

def get_p_or_n(comments): # 获取情绪极化评分，并划定阈值确定是积极、消极或中立
    with open('result.csv', 'w', encoding='utf-8') as csvfile:
        id = 0
        writer = csv.writer(csvfile)
        writer.writerow(['id', 'result', 'score', 'comment'])
        with open('samples.csv', 'w', encoding='utf-8') as samples_file:
            writer_samples = csv.writer(samples_file)
            writer_samples.writerow(['id', 'result', 'score', 'OurJudge', 'comment'])
            for each in comments:
                judge = TextBlob(each)
                # print(each)
                result = ''
                score = judge.sentiment.polarity
                if score > 0.05:
                    result = '积极'
                elif score < -0.03:
                    result = '消极'
                else:
                    result = '中立'
                id += 1
                writer.writerow([id, result, score, each])
                if id%5 == 0:
                    writer_samples.writerow([id, result, score, '', each])

def main():
    filename = "comments.csv"
    comments, words = getComments(filename)
    print(len(comments))
    getWordCloud(words, "WordCloud.png")
    get_p_or_n(comments)

if __name__ == "__main__":
    main()
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56