[免费]【NLP舆情分析】基于python微博舆情分析可视化系统(flask+pandas+echarts)【论文+源码+SQL脚本】

java1234_小锋2025-07-29 16:22

大家好，我是python222_小锋老师，看到一个不错的【NLP舆情分析】基于python微博舆情分析可视化系统(flask+pandas+echarts)，分享下哈。

项目视频演示

【免费】【NLP舆情分析】基于python微博舆情分析可视化系统(flask+pandas+echarts+爬虫) Python毕业设计_哔哩哔哩_bilibili

项目介绍

随着社交媒体的快速发展，微博作为一种重要的公共信息平台，承载着大量的社会舆论和民众情感。如何有效地从微博平台获取并分析海量的舆情数据，成为了当前信息社会中的重要课题。本论文基于自然语言处理（NLP）技术，结合Flask、Pandas、ECharts和爬虫技术，设计并实现了一套微博舆情分析可视化系统。

该系统首先利用Python中的爬虫技术从微博平台实时抓取相关舆情数据，包括微博内容、评论、转发等信息。通过对抓取数据的清洗和预处理，使用Pandas进行数据分析，提取关键词、情感倾向和舆情热度等信息。接着，通过NLP技术对微博内容进行情感分析，识别出用户的情感态度（如正面、负面、中立）。最后，系统使用ECharts进行数据的可视化展示，为用户提供直观、动态的舆情分析图表，帮助决策者实时掌握舆情走向。

系统不仅能够有效地获取和分析微博上的实时舆情信息，还提供了良好的交互性和可操作性，用户可以根据需要进行舆情趋势分析、情感分布展示及关键词云等操作。通过对实际案例的分析验证，系统具有较高的准确性和实用性，能够帮助相关部门及时识别网络舆论的动态变化，并做出相应的应对措施。

本论文的研究成果为基于Python的舆情分析系统提供了一种新的实现思路，具有广泛的应用前景，尤其在公共事务管理、品牌舆情监控以及社会热点事件的监测中具有重要的实际意义。

系统展示

部分代码

python 复制代码 
import pandas as pd
from flask import Blueprint, render_template, jsonify, request
from snownlp import SnowNLP

from dao import articleDao, commentDao
from util import wordcloudUtil, mapUtil

pb = Blueprint('page', __name__, url_prefix='/page', template_folder='templates')


@pb.route('/home')
def home():
    """
    进入主页面，获取相应的数据，带到页面去
    :return:
    """
    articleData = articleDao.get7DayArticle()
    xAxis7ArticleData = []
    yAxis7ArticleData = []
    for article in articleData:
        xAxis7ArticleData.append(article[0])
        yAxis7ArticleData.append(article[1])

    # 获取帖子类别数量
    arcTypeData = []
    articleTypeAmountList = articleDao.getArticleTypeAmount()
    for arcType in articleTypeAmountList:
        arcTypeData.append({'value': arcType[1], 'name': arcType[0]})

    # 获取top50评论用户名
    top50CommentUserList = commentDao.getTopCommentUser()
    top50CommentUserNameList = [cu[0] for cu in top50CommentUserList]
    str = ' '.join(top50CommentUserNameList)
    wordcloudUtil.genWordCloudPic(str, 'comment_mask.jpg', 'comment_user_cloud.jpg')

    # 获取7天评论数量
    commentData = []
    commentAmountList = commentDao.getCommentAmount()
    for comment in commentAmountList:
        commentData.append({'value': comment[1], 'name': comment[0]})
    return render_template('index.html',
                           xAxis7ArticleData=xAxis7ArticleData,
                           yAxis7ArticleData=yAxis7ArticleData,
                           arcTypeData=arcTypeData,
                           commentData=commentData)


@pb.route('homePageData')
def getHomePageData():
    """
    获取主页数据 ajax异步交互 前端每隔5分钟请求一次 实时数据
    :return:
    """
    totalArticle = articleDao.getTotalArticle()
    topAuthor = articleDao.getTopAuthor()
    topRegion = articleDao.getTopRegion()
    topArticles = articleDao.getArticleTopZan()
    return jsonify(totalArticle=totalArticle, topAuthor=topAuthor, topRegion=topRegion, topArticles=topArticles)


@pb.route('hotWord')
def hotWord():
    """
    热词分析统计
    :return:
    """
    hotwordList = []
    # 只读取前100条
    df = pd.read_csv('./fenci/comment_fre.csv', nrows=100)
    for value in df.values:
        hotwordList.append(value[0])
    # 获取请求参数，如果没有获取到，给个默认值 第一个列表数据
    defaultHotWord = request.args.get('word', default=hotwordList[0])
    hotwordNum = 0  # 出现次数
    for value in df.values:
        if defaultHotWord == value[0]:
            hotwordNum = value[1]

    # 情感分析
    sentiments = ''
    stc = SnowNLP(defaultHotWord).sentiments
    if stc > 0.6:
        sentiments = '正面'
    elif stc < 0.2:
        sentiments = '负面'
    else:
        sentiments = '中性'

    commentHotWordData = commentDao.getCommentHotWordAmount(defaultHotWord)
    xAxisHotWordData = []
    yAxisHotWordData = []
    for comment in commentHotWordData:
        xAxisHotWordData.append(comment[0])
        yAxisHotWordData.append(comment[1])

    commentList = commentDao.getCommentByHotWord(defaultHotWord)
    return render_template('hotWord.html',
                           hotwordList=hotwordList,
                           defaultHotWord=defaultHotWord,
                           hotwordNum=hotwordNum,
                           sentiments=sentiments,
                           xAxisHotWordData=xAxisHotWordData,
                           yAxisHotWordData=yAxisHotWordData,
                           commentList=commentList)


@pb.route('articleData')
def articleData():
    """
    微博舆情分析
    :return:
    """
    articleOldList = articleDao.getAllArticle()
    articleNewList = []
    for article in articleOldList:
        article = list(article)
        # 情感分析
        sentiments = ''
        stc = SnowNLP(article[1]).sentiments
        if stc > 0.6:
            sentiments = '正面'
        elif stc < 0.2:
            sentiments = '负面'
        else:
            sentiments = '中性'
        article.append(sentiments)
        articleNewList.append(article)
    return render_template('articleData.html', articleList=articleNewList)


@pb.route('articleDataAnalysis')
def articleDataAnalysis():
    """
    微博数据分析
    :return:
    """
    arcTypeList = []
    df = pd.read_csv('./spider/arcType_data.csv')
    for value in df.values:
        arcTypeList.append(value[0])
    # 获取请求参数，如果没有获取到，给个默认值 第一个列表数据
    defaultArcType = request.args.get('arcType', default=arcTypeList[0])
    articleList = articleDao.getArticleByArcType(defaultArcType)
    xDzData = []  # 点赞x轴数据
    xPlData = []  # 评论x轴数据
    xZfData = []  # 转发x轴数据
    rangeNum = 1000
    rangeNum2 = 100
    for item in range(0, 10):
        xDzData.append(str(rangeNum * item) + '-' + str(rangeNum * (item + 1)))
        xPlData.append(str(rangeNum * item) + '-' + str(rangeNum * (item + 1)))
    for item in range(0, 20):
        xZfData.append(str(rangeNum2 * item) + '-' + str(rangeNum2 * (item + 1)))
    xDzData.append('1万+')
    xPlData.append('1万+')
    xZfData.append('2千+')
    yDzData = [0 for x in range(len(xDzData))]  # 点赞y轴数据
    yPlData = [0 for x in range(len(xPlData))]  # 评论y轴数据
    yZfData = [0 for x in range(len(xZfData))]  # 转发y轴数据
    for article in articleList:
        for item in range(len(xDzData)):
            if int(article[4]) < rangeNum * (item + 1):
                yDzData[item] += 1
                break
            elif int(article[4]) > 10000:
                yDzData[len(xDzData) - 1] += 1
                break
            if int(article[3]) < rangeNum * (item + 1):
                yPlData[item] += 1
                break
            elif int(article[3]) > 10000:
                yPlData[len(xDzData) - 1] += 1
                break

    for article in articleList:
        for item in range(len(xZfData)):
            if int(article[2]) < rangeNum2 * (item + 1):
                yZfData[item] += 1
                break
            elif int(article[2]) > 2000:
                yZfData[len(xZfData) - 1] += 1
                break
    return render_template('articleDataAnalysis.html',
                           arcTypeList=arcTypeList,
                           defaultArcType=defaultArcType,
                           xDzData=xDzData,
                           yDzData=yDzData,
                           xPlData=xPlData,
                           yPlData=yPlData,
                           xZfData=xZfData,
                           yZfData=yZfData)


@pb.route('commentDataAnalysis')
def commentDataAnalysis():
    """
    微博评论数据分析
    :return:
    """
    commentList = commentDao.getAllComment()
    xDzData = []  # 点赞X轴数据
    rangeNum = 5
    for item in range(0, 20):
        xDzData.append(str(rangeNum * item) + '-' + str(rangeNum * (item + 1)))
    xDzData.append('1百+')
    yDzData = [0 for x in range(len(xDzData))]  # 点赞y轴数据
    genderDic = {'男': 0, '女': 0}
    for comment in commentList:
        for item in range(len(xDzData)):
            if int(comment[4]) < rangeNum * (item + 1):
                yDzData[item] += 1
                break
            elif int(comment[4]) > 100:
                yDzData[len(xDzData) - 1] += 1
                break
            if genderDic.get(comment[8], -1) != -1:
                genderDic[comment[8]] += 1
    genderData = [{'name': x[0], 'value': x[1]} for x in genderDic.items()]

    # 只读取前50条数据
    df = pd.read_csv('./fenci/comment_fre.csv', nrows=50)
    hotCommentwordList = [x[0] for x in df.values]
    str2 = ' '.join(hotCommentwordList)
    wordcloudUtil.genWordCloudPic(str2, 'comment_mask.jpg', 'comment_cloud.jpg')
    return render_template('commentDataAnalysis.html',
                           xDzData=xDzData,
                           yDzData=yDzData,
                           genderData=genderData)


@pb.route('articleCloud')
def articleCloud():
    """
    微博内容词云图
    :return:
    """
    # 只读取前50条数据
    df = pd.read_csv('./fenci/article_fre.csv', nrows=50)
    hotArticlewordList = [x[0] for x in df.values]
    str2 = ' '.join(hotArticlewordList)
    wordcloudUtil.genWordCloudPic(str2, 'article_mask.jpg', 'article_cloud.jpg')
    return render_template('articleCloud.html')


@pb.route('commentCloud')
def commentCloud():
    """
    微博评论词云图
    :return:
    """
    # 只读取前50条数据
    df = pd.read_csv('./fenci/comment_fre.csv', nrows=50)
    hotCommentwordList = [x[0] for x in df.values]
    str2 = ' '.join(hotCommentwordList)
    wordcloudUtil.genWordCloudPic(str2, 'comment_mask.jpg', 'comment_cloud.jpg')
    return render_template('commentCloud.html')


@pb.route('commentUserCloud')
def commentUserCloud():
    """
    微博评论用户词云图
    :return:
    """
    # 获取top50评论用户名
    top50CommentUserList = commentDao.getTopCommentUser()
    top50CommentUserNameList = [cu[0] for cu in top50CommentUserList]
    str = ' '.join(top50CommentUserNameList)
    wordcloudUtil.genWordCloudPic(str, 'comment_mask.jpg', 'comment_user_cloud.jpg')
    return render_template('commentUserCloud.html')


@pb.route('ipDataAnalysis')
def ipDataAnalysis():
    """
    IP地址数据分析
    :return:
    """
    cityDic = {}  # 微博文章作者IP
    cityList = mapUtil.cityList
    articleList = articleDao.getAllArticle()
    for article in articleList:
        if article[5]:
            for city in cityList:
                if city['province'].find(article[5]) != -1:
                    if cityDic.get(city['province'], -1) == -1:
                        cityDic[city['province']] = 1
                    else:
                        cityDic[city['province']] += 1
    articleCityDicList = [{'name': x[0], 'value': x[1]} for x in cityDic.items()]

    cityDic2 = {}  # 微博评论作者IP
    commentList = commentDao.getAllComment()
    for comment in commentList:
        if comment[3]:
            for city in cityList:
                if city['province'].find(comment[3]) != -1:
                    if cityDic2.get(city['province'], -1) == -1:
                        cityDic2[city['province']] = 1
                    else:
                        cityDic2[city['province']] += 1
    commentCityDicList = [{'name': x[0], 'value': x[1]} for x in cityDic2.items()]
    return render_template('ipDataAnalysis.html',
                           articleCityDicList=articleCityDicList,
                           commentCityDicList=commentCityDicList)


@pb.route('sentimentAnalysis')
def sentimentAnalysis():
    """
    舆情数据分析
    :return:
    """
    xHotBarData = ['正面', '中性', '负面']
    yHotBarData = [0, 0, 0]
    # 只读取前100条
    df = pd.read_csv('./fenci/comment_fre.csv', nrows=100)
    for value in df.values:
        # 情感分析
        stc = SnowNLP(value[0]).sentiments
        if stc > 0.6:
            yHotBarData[0] += 1
        elif stc < 0.2:
            yHotBarData[2] += 1
        else:
            yHotBarData[1] += 1

    hotTreeMapData = [{
        'name': xHotBarData[0],
        'value': yHotBarData[0]
    }, {
        'name': xHotBarData[1],
        'value': yHotBarData[1]
    }, {
        'name': xHotBarData[2],
        'value': yHotBarData[2]
    }]

    commentPieData = [{
        'name': '正面',
        'value': 0
    }, {
        'name': '中性',
        'value': 0
    }, {
        'name': '负面',
        'value': 0
    }]
    articlePieData = [{
        'name': '正面',
        'value': 0
    }, {
        'name': '中性',
        'value': 0
    }, {
        'name': '负面',
        'value': 0
    }]
    commentList = commentDao.getAllComment()
    for comment in commentList:
        # 情感分析
        stc = SnowNLP(comment[1]).sentiments
        if stc > 0.6:
            commentPieData[0]['value'] += 1
        elif stc < 0.2:
            commentPieData[2]['value'] += 1
        else:
            commentPieData[1]['value'] += 1

    articleList = articleDao.getAllArticle()
    for article in articleList:
        # 情感分析
        stc = SnowNLP(article[1]).sentiments
        if stc > 0.6:
            articlePieData[0]['value'] += 1
        elif stc < 0.2:
            articlePieData[2]['value'] += 1
        else:
            articlePieData[1]['value'] += 1

    df2 = pd.read_csv('./fenci/comment_fre.csv', nrows=15)
    xhotData15 = [x[0] for x in df2.values][::-1]
    yhotData15 = [x[1] for x in df2.values][::-1]
    return render_template('sentimentAnalysis.html',
                           xHotBarData=xHotBarData,
                           yHotBarData=yHotBarData,
                           hotTreeMapData=hotTreeMapData,
                           commentPieData=commentPieData,
                           articlePieData=articlePieData,
                           xhotData15=xhotData15,
                           yhotData15=yhotData15)
python 复制代码 
<!doctype html>
<html lang="en">
<head>
    <meta charset="utf-8">
    <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
    <title>用户登录</title>
    <link rel="shortcut icon" href="{{ url_for('static', filename='favicon.ico') }}" type="image/x-icon">
    <link rel="stylesheet" href="/static/css/backend-plugin.min.css">
    <link rel="stylesheet" href="/static/css/backend.css">
</head>
<body class=" ">
<!-- loader Start -->
<div id="loading">
    <div id="loading-center">
    </div>
</div>
<!-- loader END -->

<div class="wrapper">
    <section class="login-content">
        <div class="container h-100">
            <div class="row align-items-center justify-content-center h-100">
                <div class="col-md-5">
                    <div class="card p-3">
                        <div class="card-body">
                            <div class="auth-logo">
                                <img src="/static/picture/logo.png" class="img-fluid  rounded-normal  darkmode-logo"
                                     alt="logo">
                                <img src="/static/picture/logo-dark.png" class="img-fluid rounded-normal light-logo"
                                     alt="logo">
                            </div>
                            <h3 class="mb-3 font-weight-bold text-center">用户登录</h3>


                            <div class="mb-5">
                                <p class="line-around text-secondary mb-0"><span
                                        class="line-around-1">微博舆情分析管理系统</span>
                                </p>
                            </div>
                            <form>
                                <div class="row">
                                    <div class="col-lg-12">
                                        <div class="form-group">
                                            <label class="text-secondary">用户名：</label>
                                            <input class="form-control" id="username" name="username" type="text"
                                                   placeholder="请输入用户名...">
                                        </div>
                                    </div>
                                    <div class="col-lg-12 mt-2">
                                        <div class="form-group">
                                            <div class="d-flex justify-content-between align-items-center">
                                                <label class="text-secondary">密码：</label>
                                            </div>
                                            <input class="form-control" id="password" name="password" type="password"
                                                   placeholder="请输入密码...">
                                        </div>
                                    </div>
                                </div>
                                <button type="button" class="btn btn-primary btn-block mt-2" onclick="submitForm()">
                                    登录
                                </button>
                                <div class=" col-lg-12 mt-3">
                                    <p class="mb-0 text-center"><font id="info" color="red"></font>&nbsp;&nbsp;还没有账号?
                                        <a
                                                href="/user/register">用户注册</a></p>  

                                </div>
                            </form>
                        </div>
                    </div>
                </div>
            </div>
        </div>
    </section>
</div>
<script>
    function submitForm() {
        let username = $("#username").val()
        let password = $("#password").val()
        if (username == "") {
            $("#info").text("用户名不能为空!")
            return false;
        }
        if (password == "") {
            $("#info").text("密码不能为空!")
            return false;
        }
        $.post('/user/login', {
            'username': username,
            'password': password
        }, function (result) {
            if (result.error) {
                $("#info").text(result.info)
            } else {
                window.location.href = '/page/home';
            }
        })
    }
</script>
<!-- Backend Bundle JavaScript -->
<script src="/static/js/backend-bundle.min.js"></script>
<!-- Chart Custom JavaScript -->
<script src="/static/js/customizer.js"></script>

<script src="/static/js/sidebar.js"></script>

<!-- Flextree Javascript-->
<script src="/static/js/flex-tree.min.js"></script>
<script src="/static/js/tree.js"></script>

<!-- Table Treeview JavaScript -->
<script src="/static/js/table-treeview.js"></script>

<!-- SweetAlert JavaScript -->
<script src="/static/js/sweetalert.js"></script>

<!-- Vectoe Map JavaScript -->
<script src="/static/js/vector-map-custom.js"></script>

<!-- Chart Custom JavaScript -->
<script src="/static/js/chart-custom.js"></script>
<script src="/static/js/01.js"></script>
<script src="/static/js/02.js"></script>

<!-- slider JavaScript -->
<script src="/static/js/slider.js"></script>

<!-- Emoji picker -->
<script src="/static/js/index.js" type="module"></script>


<!-- app JavaScript -->
<script src="/static/js/app.js"></script>
</body>
</html>

源码下载

链接：https://pan.baidu.com/s/1piPhytu4YuKRBPHva2RQQg

提取码：1234

相关推荐
仰望星空的凡人14 分钟前
【JS逆向基础】数据库之MongoDB
javascript·数据库·python·mongodb
F_D_Z36 分钟前
【PyTorch】图像多分类项目部署
人工智能·pytorch·python·深度学习·分类
pingzhuyan2 小时前
python入门篇12-虚拟环境conda的安装与使用
python·ai·llm·ocr·conda
香蕉可乐荷包蛋2 小时前
排序算法 (Sorting Algorithms)-Python示例
python·算法·排序算法
菜鸟学Python4 小时前
Python web框架王者 Django 5.0发布：20周年了！
前端·数据库·python·django·sqlite
旧时光巷5 小时前
【机器学习-4】 | 集成学习 / 随机森林篇
python·随机森林·机器学习·集成学习·sklearn·boosting·bagging
Ice__Cai6 小时前
Django + Celery 详细解析：构建高效的异步任务队列
分布式·后端·python·django
MediaTea6 小时前
Python 库手册：doctest 文档测试模块
开发语言·python·log4j
2025年一定要上岸6 小时前
【pytest高阶】源码的走读方法及插件hook
运维·前端·python·pytest
angushine6 小时前
Python将Word转换为Excel
python·word·excel
热门推荐
01Qwen3-Coder 快速上手教程 | Qwen Code + Claude Code02全球最强模型Grok4，国内已可免费使用！（附教程）03Coze 开源了，送上保姆级私有化部署方案【建议收藏】04扣子开源本地部署教程 丨Coze智能体小白喂饭级指南05KGG转MP3工具|非KGM文件|解密音频06腾讯还是太全面了，限时免费！超全CodeBuddy IDE保姆级教程！（附案例）0701-开源版COZE-字节 Coze Studio 重磅开源！保姆级本地安装教程，手把手带你体验08干翻 Typora！MilkUp：完全免费的桌面端 Markdown 编辑器！09【手把手攻略】国家育儿补贴正式开领！一键算清你能拿多少钱？附补贴领取计算器10coze 开源版本地部署及踩过的坑【喂饭级教程】