102201601/emotion_analysis.py

from snownlp import SnowNLP
import matplotlib.pyplot as plt
import os
# search_word = "2024巴黎奥运会"

def emotion_aly(search_word):
    print("正在进行弹幕情感分析...")

    # 定义文件名
    file_name = f'{search_word}弹幕.txt'
    
    # 若文件不存在则停止执行
    if not os.path.exists(file_name):
        print(f"文件 {file_name} 不存在。")
        return

    # 初始化空列表
    comment_list = []

    # 读取文件并将每一行数据添加到列表
    with open(file_name, mode='r', encoding='utf-8') as f:
        comment_list = f.readlines()

    # 去除每行末尾的换行符
    comment_list = [comment.strip() for comment in comment_list]

    # 初始化情感统计
    emotions = {
        'positive': 0,
        'negative': 0,
        'neutral': 0
    }

    # 若文件为空则停止执行
    if not comment_list:
        print("弹幕文件为空，无法进行情感分析。")
        return

    # 对每条评论进行情感分析
    for comment in comment_list:
        s = SnowNLP(comment)
        if s.sentiments > 0.7:
            emotions['positive'] += 1
        elif s.sentiments < 0.3:
            emotions['negative'] += 1
        else:
            emotions['neutral'] += 1

    print(emotions)

    # 防止饼状图数据为0的情况
    if sum(emotions.values()) == 0:
        print("没有有效的情感分析数据。")
        return

    # 绘制饼状图
    colors = ['#ff9999', '#66b3ff', '#99ff99']
    plt.style.use('fivethirtyeight')
    plt.pie(emotions.values(), labels=emotions.keys(), colors=colors, autopct='%1.1f%%')
    # 调整子图的边距
    plt.subplots_adjust(top=0.901, bottom=0.044, left=0.033, right=0.967, hspace=0.2, wspace=0.2)
    plt.tight_layout()
    plt.rcParams['font.family'] = ['sans-serif']
    plt.rcParams['font.sans-serif'] = ['SimHei']
    plt.rcParams['font.size'] = 14
    plt.title(f"{search_word}弹幕情感分析图", fontsize=16)
    plt.savefig(f"{search_word}弹幕情感分析图.jpg")
    plt.show()