{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 使用自定义评分函数进行关键词提取、词频统计、词云图可视化"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 导入必要的包"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import jieba.analyse\n",
    "import math\n",
    "import numpy as np\n",
    "import jieba.posseg as pseg\n",
    "from tqdm import tqdm\n",
    "import pandas as pd\n",
    "import jieba.analyse\n",
    "import jieba.posseg as psg\n",
    "from os import path\n",
    "import matplotlib.pyplot as plt\n",
    "from wordcloud import WordCloud\n",
    "import jieba.analyse\n",
    "import pandas as pd\n",
    "import jieba"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 读取数据与数据基础信息查看"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "raw_df = pd.read_csv(r'rawdata_reprocessed.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>weibo_username</th>\n",
       "      <th>weibo_verification</th>\n",
       "      <th>weibo_content</th>\n",
       "      <th>weibo_content_preprocessed</th>\n",
       "      <th>submit_time</th>\n",
       "      <th>forward_counts</th>\n",
       "      <th>comments_counts</th>\n",
       "      <th>points_times</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>辣子鸡谁做的好吃</td>\n",
       "      <td>NaN</td>\n",
       "      <td>好像可以在自己幻想的元宇宙里过一辈子好像已经过完了一辈子双鱼座的脑子要不得</td>\n",
       "      <td>好像 幻想 元宇宙 里 一辈子 好像 完 一辈子 双鱼座 脑子 要不得</td>\n",
       "      <td>01月10日 23:59</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>远古的刀</td>\n",
       "      <td>NaN</td>\n",
       "      <td>反正闭关锁宇宙我们将会面临下一次的闭关锁国融入不了全球经济王峻涛跟你们讲我相信这个元宇宙真的...</td>\n",
       "      <td>反正 闭关 锁 宇宙 将会 面临 闭关锁国 融入 全球 经济 王峻涛 讲 元宇宙 真的 一下...</td>\n",
       "      <td>01月10日 23:58</td>\n",
       "      <td>32</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>暮景烟_深浅</td>\n",
       "      <td>NaN</td>\n",
       "      <td>周深先生之夜元宇宙周深拥有了生米就像拥有了梦的翅膀卡布叻周深放心飞吧生米永相随时尚先生元宇宙...</td>\n",
       "      <td>周深 之夜 元宇宙 周深 拥有 生米 拥有 梦 翅膀 卡布 叻 周深 放心 飞 生米 永 相...</td>\n",
       "      <td>01月10日 23:58</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>东辉毅恒传媒</td>\n",
       "      <td>NaN</td>\n",
       "      <td>王峻涛其实吧你有空可以再看看这个视频跟你们讲我相信这个元宇宙真的会来虽然不是一下子就到来还需...</td>\n",
       "      <td>王峻涛 有空 视频 讲 元宇宙 真的 一下子 到来 技术 突破 社会 讲 玩 后果 人会 分...</td>\n",
       "      <td>01月10日 23:57</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>在寒蝉鸣泣中等待夏日重现</td>\n",
       "      <td>NaN</td>\n",
       "      <td>敬元宇宙让基尔希斯坦的女朋友的微博视频</td>\n",
       "      <td>敬 元宇宙 基尔 希斯 坦 女朋友 微博 视频</td>\n",
       "      <td>01月10日 23:57</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>北北红牛一号</td>\n",
       "      <td>微博个人认证</td>\n",
       "      <td>我们在玩股票的时候首先要明白当前的市场环境大势第一顺势而为整个市场的高度从龙精药业的板并且给...</td>\n",
       "      <td>玩 股票 明白 市场 环境 大势 第一 顺势 市场 高度 从龙精 药业 板 给出 一线 逃命...</td>\n",
       "      <td>01月10日 23:56</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>-玫瑰骑士夢</td>\n",
       "      <td>微博个人认证</td>\n",
       "      <td>朝元気芋泥萄萄宇宙小居民黄仁俊元气活泼跑起来会扬起耳朵的小帕恰签售时挑战的可爱笨笨金色卷卷珍...</td>\n",
       "      <td>元 気 芋 泥 萄 萄 宇宙 居民 黄仁俊 元气 活泼 跑 扬起 耳朵 小帕恰 签售 时 挑...</td>\n",
       "      <td>01月10日 23:56</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>成都仁寿商会</td>\n",
       "      <td>NaN</td>\n",
       "      <td>元宇宙成苹果禁区将发布首款头显月日消息苹果公司预计将于今年发布其首款混合现实头戴设备彭博社记...</td>\n",
       "      <td>元宇宙 成 苹果 禁区 发布 首款 头显 月 日 消息 苹果公司 预计 发布 首款 混合 现...</td>\n",
       "      <td>01月10日 23:56</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>是个吃货叻</td>\n",
       "      <td>NaN</td>\n",
       "      <td>帅帅帅冲浪的紅豆鯊啊啊啊太帅了卡布叻周深周深星星瞭望塔周深时尚先生周深先生之夜元宇宙勇敢突破...</td>\n",
       "      <td>帅帅帅 冲浪 紅豆 鯊 啊啊啊 太帅 卡布 叻 周深 周深 星星 瞭望 塔周 深 时尚 周深...</td>\n",
       "      <td>01月10日 23:55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1026193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>是个吃货叻</td>\n",
       "      <td>NaN</td>\n",
       "      <td>周深啊啊啊啊冲浪的紅豆鯊啊啊啊太帅了卡布叻周深周深星星瞭望塔周深时尚先生周深先生之夜元宇宙勇...</td>\n",
       "      <td>周深 啊啊啊 冲浪 紅豆 鯊 啊啊啊 太帅 卡布 叻 周深 周深 星星 瞭望 塔周 深 时尚...</td>\n",
       "      <td>01月10日 23:55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1026193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>山东大A</td>\n",
       "      <td>NaN</td>\n",
       "      <td>今晚和怡宝一起玩了人类一败涂地在元宇宙也想邀请你跳一支交谊舞</td>\n",
       "      <td>今晚 怡宝 玩 人类 一败涂地 元宇宙 想 邀请 跳 一支 交谊舞</td>\n",
       "      <td>01月10日 23:53</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>养绫波的猫空</td>\n",
       "      <td>NaN</td>\n",
       "      <td>设圈到底是本身就低龄还是有人割低龄韭菜镁基夜师傅说虚拟图片我还以为元宇宙结果又是设还不如元宇...</td>\n",
       "      <td>设圈 低龄 有人 割 低龄 韭菜 镁 基夜 师傅 说 虚拟 图片 元宇宙 设 元宇宙 炒孽 ...</td>\n",
       "      <td>01月10日 23:52</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>71750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>云啸-</td>\n",
       "      <td>NaN</td>\n",
       "      <td>周深先生之夜元宇宙往事都随风而散你的歌声也飘远但是我的心不会为你而散卡布叻周深时尚先生元宇宙...</td>\n",
       "      <td>周深 之夜 元宇宙 往事 随风 而散 歌声 飘远 心 散卡布 叻 周深 时尚 元宇宙 梅涩 ...</td>\n",
       "      <td>01月10日 23:52</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>yu兔去看烸</td>\n",
       "      <td>微博个人认证</td>\n",
       "      <td>一个人的时候喜欢沉浸式唱歌尽力把感情音调动作表情等等都用上细细地把自己融入你会发现在一首歌里...</td>\n",
       "      <td>喜欢 沉浸 式 唱歌 尽力 感情 音调 动作 表情 细细地 融入 发现 一首歌 里 深层 东...</td>\n",
       "      <td>01月10日 23:51</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>馍中王</td>\n",
       "      <td>NaN</td>\n",
       "      <td>利好东北意思一边在东北开澡堂子一边玩元宇宙实体虚拟都赢麻了</td>\n",
       "      <td>利好 东北 东北 开 澡堂子 玩 元宇宙 实体 虚拟 赢 麻</td>\n",
       "      <td>01月10日 23:51</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>遂昌快活林</td>\n",
       "      <td>微博个人认证</td>\n",
       "      <td>元宇宙金融时报如果银行也来元宇宙你怎么看月日央行主管的金融时报官微发文虚拟品牌官艾雅正式入职...</td>\n",
       "      <td>元宇宙 金融时报 银行 元宇宙 月 日 央行 主管 金融时报 官微 发文 虚拟 品牌 官艾雅...</td>\n",
       "      <td>01月10日 23:50</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>元味儿冰淇淋</td>\n",
       "      <td>NaN</td>\n",
       "      <td>一往无前的蓝张嘉元宇宙没有伏笔海里没有潮汐请问你是在搜张嘉元的宇宙海吗既然来了那就了解一下元...</td>\n",
       "      <td>一往无前 蓝 张嘉 元宇宙 伏笔 海里 潮汐 请问 搜 张嘉元 宇宙 海 元气 满满的 指弹...</td>\n",
       "      <td>01月10日 23:49</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>见闻实时新闻</td>\n",
       "      <td>微博官方认证</td>\n",
       "      <td>人民日报评论无论元宇宙和人工智能多么精彩但或许最难冲击甚至取代洗浴行业经历过竞奢赛豪的误区如...</td>\n",
       "      <td>人民日报 评论 元宇宙 人工智能 精彩 难 冲击 取代 洗浴 行业 经历 竞奢赛 豪 误区 ...</td>\n",
       "      <td>01月10日 23:48</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>拉诺西亚香橙</td>\n",
       "      <td>NaN</td>\n",
       "      <td>镁基夜师傅说虚拟图片我还以为元宇宙结果又是设还不如元宇宙呢那个还能炒孽孽没有猫迷惑行為大賞小...</td>\n",
       "      <td>镁 基夜 师傅 说 虚拟 图片 元宇宙 设 元宇宙 炒孽 孽 猫 迷惑 行為 大賞 幽困 呼...</td>\n",
       "      <td>01月10日 23:48</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>71750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>心台怡的怡4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>繁體君周深时尚先生卡布叻周深周深星轨记录仪周深周深年度先生走过荆棘丛生夜色茫茫仍有理想滚烫心...</td>\n",
       "      <td>繁體 君 周深 时尚 卡布 叻 周深 周深 星轨 记录仪 周深 周深 年度 走过 荆棘丛生 ...</td>\n",
       "      <td>01月10日 23:48</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1026193</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   weibo_username weibo_verification  \\\n",
       "0        辣子鸡谁做的好吃                NaN   \n",
       "1            远古的刀                NaN   \n",
       "2          暮景烟_深浅                NaN   \n",
       "3          东辉毅恒传媒                NaN   \n",
       "4    在寒蝉鸣泣中等待夏日重现                NaN   \n",
       "5          北北红牛一号             微博个人认证   \n",
       "6          -玫瑰骑士夢             微博个人认证   \n",
       "7          成都仁寿商会                NaN   \n",
       "8           是个吃货叻                NaN   \n",
       "9           是个吃货叻                NaN   \n",
       "10           山东大A                NaN   \n",
       "11         养绫波的猫空                NaN   \n",
       "12            云啸-                NaN   \n",
       "13         yu兔去看烸             微博个人认证   \n",
       "14            馍中王                NaN   \n",
       "15          遂昌快活林             微博个人认证   \n",
       "16         元味儿冰淇淋                NaN   \n",
       "17         见闻实时新闻             微博官方认证   \n",
       "18         拉诺西亚香橙                NaN   \n",
       "19         心台怡的怡4                NaN   \n",
       "\n",
       "                                        weibo_content  \\\n",
       "0               好像可以在自己幻想的元宇宙里过一辈子好像已经过完了一辈子双鱼座的脑子要不得   \n",
       "1   反正闭关锁宇宙我们将会面临下一次的闭关锁国融入不了全球经济王峻涛跟你们讲我相信这个元宇宙真的...   \n",
       "2   周深先生之夜元宇宙周深拥有了生米就像拥有了梦的翅膀卡布叻周深放心飞吧生米永相随时尚先生元宇宙...   \n",
       "3   王峻涛其实吧你有空可以再看看这个视频跟你们讲我相信这个元宇宙真的会来虽然不是一下子就到来还需...   \n",
       "4                                 敬元宇宙让基尔希斯坦的女朋友的微博视频   \n",
       "5   我们在玩股票的时候首先要明白当前的市场环境大势第一顺势而为整个市场的高度从龙精药业的板并且给...   \n",
       "6   朝元気芋泥萄萄宇宙小居民黄仁俊元气活泼跑起来会扬起耳朵的小帕恰签售时挑战的可爱笨笨金色卷卷珍...   \n",
       "7   元宇宙成苹果禁区将发布首款头显月日消息苹果公司预计将于今年发布其首款混合现实头戴设备彭博社记...   \n",
       "8   帅帅帅冲浪的紅豆鯊啊啊啊太帅了卡布叻周深周深星星瞭望塔周深时尚先生周深先生之夜元宇宙勇敢突破...   \n",
       "9   周深啊啊啊啊冲浪的紅豆鯊啊啊啊太帅了卡布叻周深周深星星瞭望塔周深时尚先生周深先生之夜元宇宙勇...   \n",
       "10                     今晚和怡宝一起玩了人类一败涂地在元宇宙也想邀请你跳一支交谊舞   \n",
       "11  设圈到底是本身就低龄还是有人割低龄韭菜镁基夜师傅说虚拟图片我还以为元宇宙结果又是设还不如元宇...   \n",
       "12  周深先生之夜元宇宙往事都随风而散你的歌声也飘远但是我的心不会为你而散卡布叻周深时尚先生元宇宙...   \n",
       "13  一个人的时候喜欢沉浸式唱歌尽力把感情音调动作表情等等都用上细细地把自己融入你会发现在一首歌里...   \n",
       "14                      利好东北意思一边在东北开澡堂子一边玩元宇宙实体虚拟都赢麻了   \n",
       "15  元宇宙金融时报如果银行也来元宇宙你怎么看月日央行主管的金融时报官微发文虚拟品牌官艾雅正式入职...   \n",
       "16  一往无前的蓝张嘉元宇宙没有伏笔海里没有潮汐请问你是在搜张嘉元的宇宙海吗既然来了那就了解一下元...   \n",
       "17  人民日报评论无论元宇宙和人工智能多么精彩但或许最难冲击甚至取代洗浴行业经历过竞奢赛豪的误区如...   \n",
       "18  镁基夜师傅说虚拟图片我还以为元宇宙结果又是设还不如元宇宙呢那个还能炒孽孽没有猫迷惑行為大賞小...   \n",
       "19  繁體君周深时尚先生卡布叻周深周深星轨记录仪周深周深年度先生走过荆棘丛生夜色茫茫仍有理想滚烫心...   \n",
       "\n",
       "                           weibo_content_preprocessed   submit_time  \\\n",
       "0                 好像 幻想 元宇宙 里 一辈子 好像 完 一辈子 双鱼座 脑子 要不得  01月10日 23:59   \n",
       "1   反正 闭关 锁 宇宙 将会 面临 闭关锁国 融入 全球 经济 王峻涛 讲 元宇宙 真的 一下...  01月10日 23:58   \n",
       "2   周深 之夜 元宇宙 周深 拥有 生米 拥有 梦 翅膀 卡布 叻 周深 放心 飞 生米 永 相...  01月10日 23:58   \n",
       "3   王峻涛 有空 视频 讲 元宇宙 真的 一下子 到来 技术 突破 社会 讲 玩 后果 人会 分...  01月10日 23:57   \n",
       "4                             敬 元宇宙 基尔 希斯 坦 女朋友 微博 视频  01月10日 23:57   \n",
       "5   玩 股票 明白 市场 环境 大势 第一 顺势 市场 高度 从龙精 药业 板 给出 一线 逃命...  01月10日 23:56   \n",
       "6   元 気 芋 泥 萄 萄 宇宙 居民 黄仁俊 元气 活泼 跑 扬起 耳朵 小帕恰 签售 时 挑...  01月10日 23:56   \n",
       "7   元宇宙 成 苹果 禁区 发布 首款 头显 月 日 消息 苹果公司 预计 发布 首款 混合 现...  01月10日 23:56   \n",
       "8   帅帅帅 冲浪 紅豆 鯊 啊啊啊 太帅 卡布 叻 周深 周深 星星 瞭望 塔周 深 时尚 周深...  01月10日 23:55   \n",
       "9   周深 啊啊啊 冲浪 紅豆 鯊 啊啊啊 太帅 卡布 叻 周深 周深 星星 瞭望 塔周 深 时尚...  01月10日 23:55   \n",
       "10                  今晚 怡宝 玩 人类 一败涂地 元宇宙 想 邀请 跳 一支 交谊舞  01月10日 23:53   \n",
       "11  设圈 低龄 有人 割 低龄 韭菜 镁 基夜 师傅 说 虚拟 图片 元宇宙 设 元宇宙 炒孽 ...  01月10日 23:52   \n",
       "12  周深 之夜 元宇宙 往事 随风 而散 歌声 飘远 心 散卡布 叻 周深 时尚 元宇宙 梅涩 ...  01月10日 23:52   \n",
       "13  喜欢 沉浸 式 唱歌 尽力 感情 音调 动作 表情 细细地 融入 发现 一首歌 里 深层 东...  01月10日 23:51   \n",
       "14                     利好 东北 东北 开 澡堂子 玩 元宇宙 实体 虚拟 赢 麻  01月10日 23:51   \n",
       "15  元宇宙 金融时报 银行 元宇宙 月 日 央行 主管 金融时报 官微 发文 虚拟 品牌 官艾雅...  01月10日 23:50   \n",
       "16  一往无前 蓝 张嘉 元宇宙 伏笔 海里 潮汐 请问 搜 张嘉元 宇宙 海 元气 满满的 指弹...  01月10日 23:49   \n",
       "17  人民日报 评论 元宇宙 人工智能 精彩 难 冲击 取代 洗浴 行业 经历 竞奢赛 豪 误区 ...  01月10日 23:48   \n",
       "18  镁 基夜 师傅 说 虚拟 图片 元宇宙 设 元宇宙 炒孽 孽 猫 迷惑 行為 大賞 幽困 呼...  01月10日 23:48   \n",
       "19  繁體 君 周深 时尚 卡布 叻 周深 周深 星轨 记录仪 周深 周深 年度 走过 荆棘丛生 ...  01月10日 23:48   \n",
       "\n",
       "    forward_counts  comments_counts  points_times  \n",
       "0                0                0             0  \n",
       "1               32                3             0  \n",
       "2                0                0             0  \n",
       "3                0                0             0  \n",
       "4                0                0             5  \n",
       "5                0                0             2  \n",
       "6                0                0             0  \n",
       "7                0                0             0  \n",
       "8                0                0       1026193  \n",
       "9                0                0       1026193  \n",
       "10               0                3             3  \n",
       "11               0                0         71750  \n",
       "12               0                0             0  \n",
       "13               0                2             3  \n",
       "14               0                0            34  \n",
       "15               1                0             8  \n",
       "16               0                0             0  \n",
       "17              18               13            34  \n",
       "18               0                0         71750  \n",
       "19               0                0       1026193  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw_df.head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 进行词频统计与关键词提取"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "word_count = {}\n",
    "# contents = raw_df['weibo_content_preprocessed'].values\n",
    "# for line in tqdm(contents):\n",
    "#     words = str(line).split(' ')\n",
    "#     for word in words:\n",
    "#         if word_count.get(word) is None:\n",
    "#             word_count[word] = 1\n",
    "#         else:\n",
    "#             word_count[word] = word_count[word]+1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "词语重要性 ：  \n",
    "认证：普通用户博文中出现：1分，个人认证博文中出现：3分，官方认证博文中出现：9分  \n",
    "转评赞数据：ceil(1xlog(点赞数+1)),ceil(3xlog(评论数+1)),ceil(5xlog(转发数+1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "def auth_map(x):\n",
    "    if x == '微博个人认证':\n",
    "        return 3\n",
    "    elif x == '微博官方认证':\n",
    "        return 9\n",
    "    else:\n",
    "        return 1\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_score(df):\n",
    "    score1 = df['points_times'].map(float).map(lambda x:math.ceil(math.log10(x+1)))\n",
    "    score2 = df['comments_counts'].map(float).map(lambda x:3*math.ceil(math.log10(x+1)))\n",
    "    score3 = df['forward_counts'].map(float).map(lambda x:5*math.ceil(math.log10(x+1)))\n",
    "    score4 = df['weibo_verification'].map(auth_map)\n",
    "    score = score1+score2+score3+score4\n",
    "    return score"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 获取每一条微博的权重"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0          1\n",
       "1         14\n",
       "2          1\n",
       "3          1\n",
       "4          2\n",
       "          ..\n",
       "132199     1\n",
       "132200     5\n",
       "132201     8\n",
       "132202     1\n",
       "132203     1\n",
       "Length: 132204, dtype: int64"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scores = get_score(raw_df)\n",
    "scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "pos_allow=['d','n','ns','nr','x','vn']\n",
    "jieba.load_userdict('./userdic.txt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "def pos_filter(line:str,pos_list):\n",
    "    words = pseg.cut(str(line))\n",
    "    ret_words = []\n",
    "    for word,pos in words:\n",
    "        if word.strip() is not ''  and pos in pos_list :\n",
    "            ret_words.append(word)\n",
    "    return ret_words\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['幻想', '元宇宙', '脑子']\n"
     ]
    }
   ],
   "source": [
    "print(pos_filter('好像 幻想 元宇宙 里 一辈子 好像 完 一辈子 双鱼座 脑子 要不得',pos_allow))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 关键词提取与词频统计"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 132204/132204 [18:43<00:00, 117.70it/s]\n"
     ]
    }
   ],
   "source": [
    "keywords = dict()\n",
    "contents = raw_df['weibo_content_preprocessed'].values\n",
    "for line,score in  tqdm(zip(contents,scores),total=len(scores)):\n",
    "    # words = str(line).split(' ')\n",
    "    words = pos_filter(line,pos_allow)\n",
    "    for word in words:\n",
    "        if keywords.get(word) is None:\n",
    "            keywords[word] = score\n",
    "        else:\n",
    "            keywords[word] = keywords[word]+score\n",
    "        \n",
    "        if word_count.get(word) is None:\n",
    "            word_count[word] = 1\n",
    "        else:\n",
    "            word_count[word] = word_count[word]+1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 关键词可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "sorted_kw_dic = sorted(keywords.items(),key=lambda x:x[1],reverse=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('元宇宙', 1253941)\n",
      "('数字', 219828)\n",
      "('板块', 169289)\n",
      "('公司', 166277)\n",
      "('科技', 145733)\n",
      "('市场', 144216)\n",
      "('游戏', 141704)\n",
      "('博', 138929)\n",
      "('概念', 134401)\n",
      "('技术', 130308)\n",
      "('视频', 123068)\n",
      "('世界', 120218)\n",
      "('宇宙', 115196)\n",
      "('链接', 114956)\n",
      "('股份', 101712)\n",
      "('发展', 100481)\n",
      "('网页', 100385)\n",
      "('区块', 99274)\n",
      "('链', 98543)\n",
      "('平台', 96583)\n",
      "('币', 93274)\n",
      "('中国', 88953)\n",
      "('投资', 85720)\n",
      "('行业', 77912)\n",
      "('项目', 72632)\n",
      "('资金', 67973)\n",
      "('机会', 64881)\n",
      "('藏品', 61611)\n",
      "('现实', 59984)\n",
      "('经济', 59504)\n",
      "('行情', 57754)\n",
      "('全球', 57061)\n",
      "('互联网', 56280)\n",
      "('时间', 56272)\n",
      "('领域', 54710)\n",
      "('产品', 54643)\n",
      "('个股', 53355)\n",
      "('方向', 52531)\n",
      "('体验', 52334)\n",
      "('指数', 51934)\n",
      "('企业', 51579)\n",
      "('股票', 51557)\n",
      "('产业', 51183)\n",
      "('货币', 50009)\n",
      "('空间', 49895)\n",
      "('财经', 49673)\n",
      "('数据', 47371)\n",
      "('社区', 46818)\n",
      "('汽车', 46393)\n",
      "('时代', 46160)\n"
     ]
    }
   ],
   "source": [
    "words_frequence = dict()\n",
    "for i in range(50):\n",
    "    words_frequence[sorted_kw_dic[i][0]] = sorted_kw_dic[i][1]\n",
    "    print(sorted_kw_dic[i])\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'元宇宙': 1253941,\n",
       " '数字': 219828,\n",
       " '板块': 169289,\n",
       " '公司': 166277,\n",
       " '科技': 145733,\n",
       " '市场': 144216,\n",
       " '游戏': 141704,\n",
       " '博': 138929,\n",
       " '概念': 134401,\n",
       " '技术': 130308,\n",
       " '视频': 123068,\n",
       " '世界': 120218,\n",
       " '宇宙': 115196,\n",
       " '链接': 114956,\n",
       " '股份': 101712,\n",
       " '发展': 100481,\n",
       " '网页': 100385,\n",
       " '区块': 99274,\n",
       " '链': 98543,\n",
       " '平台': 96583,\n",
       " '币': 93274,\n",
       " '中国': 88953,\n",
       " '投资': 85720,\n",
       " '行业': 77912,\n",
       " '项目': 72632,\n",
       " '资金': 67973,\n",
       " '机会': 64881,\n",
       " '藏品': 61611,\n",
       " '现实': 59984,\n",
       " '经济': 59504,\n",
       " '行情': 57754,\n",
       " '全球': 57061,\n",
       " '互联网': 56280,\n",
       " '时间': 56272,\n",
       " '领域': 54710,\n",
       " '产品': 54643,\n",
       " '个股': 53355,\n",
       " '方向': 52531,\n",
       " '体验': 52334,\n",
       " '指数': 51934,\n",
       " '企业': 51579,\n",
       " '股票': 51557,\n",
       " '产业': 51183,\n",
       " '货币': 50009,\n",
       " '空间': 49895,\n",
       " '财经': 49673,\n",
       " '数据': 47371,\n",
       " '社区': 46818,\n",
       " '汽车': 46393,\n",
       " '时代': 46160}"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "words_frequence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x157253860f0>"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "backgroud_Image=plt.imread(r'./METAVERSE3.jpg')\n",
    "# 若是有中文的话，font_path ='simsun.ttc'必须添加，不然会出现方框，不出现汉字\n",
    "# simsun.ttc为汉字编码文件，可以从本地windows系统找一个汉字编码文件上传， 如C:\\\\Windows\\Fonts下有许多汉字编码文件\n",
    "wordcloud = WordCloud(font_path ='simsun.ttc',repeat=True,mask=backgroud_Image,background_color='white',width=2000,height=1000,colormap='cool')\n",
    "wordcloud = wordcloud.fit_words(words_frequence)\n",
    "wordcloud.to_file('wordcloud_myscoring.png')\n",
    "plt.imshow(wordcloud)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 词频可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "99192\n",
      "('元宇宙', 205648)\n",
      "('数字', 32422)\n",
      "('板块', 32068)\n",
      "('市场', 25735)\n",
      "('公司', 25269)\n",
      "('概念', 22935)\n",
      "('游戏', 22496)\n",
      "('科技', 22175)\n",
      "('技术', 20202)\n",
      "('世界', 19972)\n",
      "('宇宙', 19764)\n",
      "('博', 19030)\n",
      "('刘宇', 18907)\n",
      "('股份', 18682)\n",
      "('区块', 16620)\n",
      "('链', 16271)\n",
      "('发展', 16059)\n",
      "('链接', 15898)\n",
      "('币', 15720)\n",
      "('视频', 15678)\n",
      "('平台', 14791)\n",
      "('中国', 13560)\n",
      "('投资', 13125)\n",
      "('资金', 12942)\n",
      "('网页', 12778)\n",
      "('行业', 12605)\n",
      "('项目', 11869)\n",
      "('个股', 11369)\n",
      "('机会', 10871)\n",
      "('指数', 10713)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(len(word_count))\n",
    "sorted_wc_dic = sorted(word_count.items(),key=lambda x:x[1],reverse=True)\n",
    "x_word = []\n",
    "y_count = []\n",
    "for i in range(30):\n",
    "    x_word.append(sorted_wc_dic[i][0])\n",
    "    y_count.append(sorted_wc_dic[i][1])\n",
    "    print(sorted_wc_dic[i])\n",
    "\n",
    "def autolabel(rects):\n",
    "    for rect in rects:\n",
    "        height = rect.get_height()\n",
    "        plt.text(rect.get_x()+rect.get_width()/2.-0.35, 1.01*height, '%s' % int(height))\n",
    "\n",
    "plt.figure(figsize=(20,10))\n",
    "plt.rcParams['font.sans-serif']=['SimHei'] #用来正常显示中文标签\n",
    "plt.rcParams['axes.unicode_minus']=False #用来正常显示负号 #有中文出现的情况，需要u'内容'\n",
    "rects = plt.bar(x_word,y_count,width=0.5,color=\"c\")\n",
    "plt.xlabel(\"word\")\n",
    "plt.ylabel(\"frequency\")\n",
    "plt.yscale('symlog')\n",
    "plt.ylim(10000,250000)\n",
    "autolabel(rects)"
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "7758e92e9a61d7a3490898707f7eeb937c85e9d1e8d4e877cc6c187218f226d5"
  },
  "kernelspec": {
   "display_name": "Python 3.6.13 ('base')",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.13"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}