Tourism Comment Data Collection and Visualization Dashboard Using Python Flask

Background : Understanding tourist reviews is crucial for destination management and marketing; the project collects review data, performs sentiment analysis and keyword frequency analysis, and presents the results on a Flask‑based visualization dashboard to aid decision‑making.

Technology Stack : Flask framework, HTML/JS/CSS front‑end, MySQL 8.0, pandas, ECharts for visualization, and requests for web scraping.

Front‑end Design : The page follows HTML5 standards with a three‑column layout, includes dynamic particle effects, uses jQuery and ECharts for interactive charts, refreshes data via setInterval, and adapts to various screen sizes.

Flask Implementation (main code) :

class CorpData(SourceDataDemo):

    def __init__(self):
        """
        按照 SourceDataDemo 的格式覆盖数据即可
        """
        super().__init__()
        self.title = '旅游景点评论数据采集与可视化大屏'
        self.counter = {'name': '景点数', 'value': tj()[0]}
        self.counter2 = {'name': '评论数', 'value': tj()[1]}
        self.echart1_data = {
            'title': '套餐类型分析',
            'data': pinpai()
        }
        self.echart2_data = {
            'title': '不同景点评论数',
            'data': jiage()
        }
        self.echarts3_1_data = {
            'title': '是否VIP分析',
            'data': cpu_1()
        }
        self.echart4_data = {
            'title': '不同年份评论数对比',
            'data': [
                {"name": "数量", "value": xiaoliang()['数量']},
            ],
            'xAxis': xiaoliang()['年'],
        }
        self.echart5_data = {
            'title': '词频分析',
            'data': pm()
        }
        self.echart6_data = {
            'title': '评论数据',
            'data': biao()
        }
        self.map_1_data = {
            # 'symbolSize': 80000,
            'data': sheng()
        }

Crawler Implementation (main code) :

html = requests.post(posturl, data=json.dumps(request), headers=headers)
html1 = json.loads(html.text)
print('正在爬取第' + str(i) + '页')
items = html1['result']['items']
for k in items:
    try:
        pl = k['content']
        didian = k['ipLocatedName']
        zongping = k['publishTypeTag']
        pf1 = k['scores'][0]['name']
        pf1_score = k['scores'][0]['score']
        pf2 = k['scores'][1]['name']
        pf2_score = k['scores'][1]['score']
        pf3 = k['scores'][2]['name']
        pf3_score = k['scores'][2]['score']
        taocan = k['touristTypeDisplay']
        vip = k['userInfo']['userMember']
        print(pl, didian, zongping, pf1, pf1_score, pf2, pf2_score, pf3, pf3_score, taocan, vip)
        ws.append([pl, didian, zongping, pf1_score, pf2_score, pf3_score, taocan, vip])
    except:
        pass

Visualization Implementation (main code) :

tooltip: {
        show: true,
        formatter: function(params) {
            if (params.value.length > 1) {
                return '  ' + params.name + '   ' + params.value[2] + '热度  ';
            } else {
                return '  ' + params.name + '   ' + params.value + '热度  ';
            }
        },
    },
    geo: {
        map: 'china',
        show: true,
        roam: false,
        label: { emphasis: { show: false } },
        layoutSize: "100%",
        itemStyle: {
            normal: {
                borderColor: new echarts.graphic.LinearGradient(0, 0, 0, 1, [{
                    offset: 0,
                    color: '#00F6FF'
                }, {
                    offset: 1,
                    color: '#53D9FF'
                }], false),
                borderWidth: 3,
                shadowColor: 'rgba(10,76,139,1)',
                shadowOffsetY: 0,
                shadowBlur: 60
            }
        }
    },
    series: [{
        type: 'map',
        map: 'china',
        aspectScale: 0.75,
        label: { normal: { show: false }, emphasis: { show: false } },
        itemStyle: {
            normal: {
                areaColor: {
                    x: 0,
                    y: 0,
                    x2: 0,
                    y2: 1,
                    colorStops: [{ offset: 0, color: '#073684' }, { offset: 1, color: '#061E3D' }]
                },
                borderColor: '#215495',
                borderWidth: 1,
            },
            emphasis: { areaColor: { x: 0, y: 0, x2: 0, y2: 1, colorStops: [{ offset: 0, color: '#073684' }, { offset: 1, color: '#061E3D' }] } }
        },
        data: outdata,
    }, {
        type: 'effectScatter',
        coordinateSystem: 'geo',
        rippleEffect: { brushType: 'stroke' },
        showEffectOn: 'render',
        itemStyle: { normal: { color: { type: 'radial', x: 0.5, y: 0.5, r: 0.5, colorStops: [{ offset: 0, color: 'rgba(5,80,151,0.2)' }, { offset: 0.8, color: 'rgba(5,80,151,0.8)' }, { offset: 1, color: 'rgba(0,108,255,0.7)' }], global: false } } },
        label: { normal: { show: true, color: '#fff', fontWeight: 'bold', position: 'inside', formatter: function(para) { return '{cnNum|' + para.data.value[2] + '}'; }, rich: { cnNum: { fontSize: 13, color: '#D4EEFF' } } } },
        symbol: 'circle',
        symbolSize: function(val) {
            if (val[2] === 0) { return 0; }
            var a = (maxSize4Pin - minSize4Pin) / (max - min);
            var b = maxSize4Pin - a * max;
            return a * val[2] + b * 1.2;
        },
        data: convertData(outdata),
        zlevel: 1,
    }]
};