[NLP_06]Measure_bias_across_all_genres.ipynb

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  "metadata": {
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      "collapsed_sections": [],
      "machine_shape": "hm",
      "mount_file_id": "1-ZJFgcsZgTrq6JbwM0S1fRRW29tm8bzs",
      "authorship_tag": "ABX9TyPGEgYIREvFkx6endG94TUN",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU",
    "gpuClass": "premium"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/jx-dohwan/Aiffel_NLP_Project/blob/main/%5BNLP_06%5DMeasure_bias_across_all_genres.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# [NLP_06]Measure bias across all genres\n",
        "모든 장르에 대해 영화 구분과의 편향성 정도를 측정해 보겠습니다."
      ],
      "metadata": {
        "id": "w6k3QwClc8y_"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 데이터 설명\n",
        "\n",
        "1. 영화 구분\n",
        "  - synopsis_art.txt : 예술영화\n",
        "  - synopsis_gen.txt : 일반영화(상업영화)\n",
        "  - 그 외는 독립영화 등으로 분류됩니다.\n",
        "2. 장르 구분\n",
        "  - synopsis_SF.txt: SF\n",
        "\n",
        "  - synopsis_가족.txt: 가족\n",
        "\n",
        "  - synopsis_공연.txt: 공연\n",
        "\n",
        "  - synopsis_공포(호러).txt: 공포(호러)\n",
        "\n",
        "  - synopsis_기타.txt: 기타\n",
        "\n",
        "  - synopsis_다큐멘터리.txt: 다큐멘터리\n",
        "\n",
        "  - synopsis_드라마.txt: 드라마\n",
        "\n",
        "  - synopsis_멜로로맨스.txt: 멜로로맨스\n",
        "\n",
        "  - synopsis_뮤지컬.txt: 뮤지컬\n",
        "\n",
        "  - synopsis_미스터리.txt: 미스터리\n",
        "\n",
        "  - synopsis_범죄.txt: 범죄\n",
        "\n",
        "  - synopsis_사극.txt: 사극\n",
        "\n",
        "  - synopsis_서부극(웨스턴).txt: 서부극(웨스턴)\n",
        "\n",
        "  - synopsis_성인물(에로).txt: 성인물(에로)\n",
        "\n",
        "  - synopsis_스릴러.txt: 스릴러\n",
        "\n",
        "  - synopsis_애니메이션.txt: 애니메이션\n",
        "\n",
        "  - synopsis_액션.txt: 액션\n",
        "\n",
        "  - synopsis_어드벤처.txt: 어드벤처\n",
        "\n",
        "  - synopsis_전쟁.txt: 전쟁\n",
        "\n",
        "  - synopsis_코미디.txt: 코미디\n",
        "\n",
        "  - synopsis_판타지.txt: 판타지"
      ],
      "metadata": {
        "id": "rc6ybFNx33dF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# from google.colab import drive\n",
        "# drive.mount('/content/drive')"
      ],
      "metadata": {
        "id": "P0VMME9wZVPU"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 1. Import 및 라이브러리 설치"
      ],
      "metadata": {
        "id": "Nz7UFJl9YsNF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!sudo apt-get install -y fonts-nanum\n",
        "!sudo fc-cache -fv\n",
        "!rm ~/.cache/matplotlib -rf\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fJOczl8C2oXS",
        "outputId": "69ebdaf3-87ad-4f7b-91d4-716549b76f84"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Reading package lists... Done\n",
            "Building dependency tree       \n",
            "Reading state information... Done\n",
            "fonts-nanum is already the newest version (20170925-1).\n",
            "The following package was automatically installed and is no longer required:\n",
            "  libnvidia-common-460\n",
            "Use 'sudo apt autoremove' to remove it.\n",
            "0 upgraded, 0 newly installed, 0 to remove and 20 not upgraded.\n",
            "/usr/share/fonts: caching, new cache contents: 0 fonts, 1 dirs\n",
            "/usr/share/fonts/truetype: caching, new cache contents: 0 fonts, 3 dirs\n",
            "/usr/share/fonts/truetype/humor-sans: caching, new cache contents: 1 fonts, 0 dirs\n",
            "/usr/share/fonts/truetype/liberation: caching, new cache contents: 16 fonts, 0 dirs\n",
            "/usr/share/fonts/truetype/nanum: caching, new cache contents: 10 fonts, 0 dirs\n",
            "/usr/local/share/fonts: caching, new cache contents: 0 fonts, 0 dirs\n",
            "/root/.local/share/fonts: skipping, no such directory\n",
            "/root/.fonts: skipping, no such directory\n",
            "/var/cache/fontconfig: cleaning cache directory\n",
            "/root/.cache/fontconfig: not cleaning non-existent cache directory\n",
            "/root/.fontconfig: not cleaning non-existent cache directory\n",
            "fc-cache: succeeded\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "! pip install konlpy"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Sf_uHQL4dXLe",
        "outputId": "5d6a24ab-0923-402d-999e-6519d18da404"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: konlpy in /usr/local/lib/python3.7/dist-packages (0.6.0)\n",
            "Requirement already satisfied: numpy>=1.6 in /usr/local/lib/python3.7/dist-packages (from konlpy) (1.21.6)\n",
            "Requirement already satisfied: lxml>=4.1.0 in /usr/local/lib/python3.7/dist-packages (from konlpy) (4.9.1)\n",
            "Requirement already satisfied: JPype1>=0.7.0 in /usr/local/lib/python3.7/dist-packages (from konlpy) (1.4.0)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from JPype1>=0.7.0->konlpy) (4.1.1)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "from numpy import dot \n",
        "from numpy.linalg import norm\n",
        "from sklearn.decomposition import PCA\n",
        "import matplotlib.pyplot as plt\n",
        "import os \n",
        "from gensim.models import KeyedVectors\n",
        "from konlpy.tag import Okt\n",
        "from gensim.models import Word2Vec\n",
        "import seaborn as sns; \n",
        "from sklearn.feature_extraction.text import TfidfVectorizer\n",
        "plt.rc('font', family='NanumBarunGothic')"
      ],
      "metadata": {
        "id": "qP7tfQcbZXY8"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "base_path = '/content/drive/MyDrive/인공지능/아이펠/GoingDeeper/학습용/data/word_embedding/weat/'"
      ],
      "metadata": {
        "id": "F1A5DBBHczcY"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 2. 형태소 분석기를 이용하여 품사가 명사인 경우 해당 단어를 추출하기"
      ],
      "metadata": {
        "id": "NyaYouqJYvgL"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "with open(base_path + 'synopsis.txt', 'r') as file:\n",
        "    for i in range(20):\n",
        "        print(file.readline(), end='')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UEd8aD_udy21",
        "outputId": "8c600201-2549-4e81-f61d-cbf995eec4a0"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "사운드 엔지니어 상우(유지태 분)는 치매에 걸린 할머니(백성희 분)와\n",
            " 젊은 시절 상처한 한 아버지(박인환 분), 고모(신신애 분)와 함께 살고 있다.\n",
            " 어느 겨울 그는 지방 방송국 라디오 PD 은수(이영애 분)를 만난다.\n",
            " 자연의 소리를 채집해 틀어주는 라디오 프로그램을 준비하는 은수는 상우와 녹음 여행을 떠난다.\n",
            " 자연스레 가까워지는 두 사람은 어느 날, 은수의 아파트에서 밤을 보낸다.\n",
            " 너무 쉽게 사랑에 빠진 두 사람... 상우는 주체할 수 없을 정도로 그녀에게 빨려든다.\n",
            " 그러나 겨울에 만난 두 사람의 관계는 봄을 지나 여름을 맞이하면서 삐걱거린다.\n",
            " 이혼 경험이 있는 은수는 상우에게 결혼할 생각이 없다며 부담스러운 표정을 내비친다.\n",
            " \"어떻게 사랑이 변하니?...\"라고 묻는 상우에게 은수는 그저 \"헤어져\" 라고 단호하게 말한다.\n",
            " 영원히 변할 것 같지 않던 사랑이 변하고, 그 사실을 받아들이지 못하는 상우는 어찌 할 바를 모른다.\n",
            " 은수를 잊지 못하는 상우는 미련과 집착의 감정을 이기지 못하고 서울과 강릉을 오간다.\n",
            "유사 이래 연령, 성별, 빈부의 차이와 정치적인 입장을 불문하고 일거에 국민을 통합해 온 '애국심'이라는 성역에 일침을 가하는 다큐멘터리. 재작년 전국 민족민주 유가족협의회의 장기농성을 다룬 인상적인 다큐멘터리 <민들레>를 만들었던 독립영화집단 '빨간 눈사람'이 우리 사회 구석구석을 발빠르게 돌아다니며 애국심과 민족주의가 강요되는 현장을 발굴하여 카메라에 담았다. 박홍 서강대 명예총장, 이도형 '한국논단' 발행인, 축구해설자 신문선, 홍세화, 박노해 등 사회 각계의 '스타'들이 등장해 저마다의 확고한 신념을 성토한다. 감독 이경순과 최하동하는 이 작품을 위해 3년간 백여 명을 인터뷰했다고 한다. 2001 올해의 독립영화상 수상.\n",
            " 민족과 국가란 공동체에서 부단히 권력과 부를 얻는 자, 나아가 민족과 국가란 공동체에서 얻은 신분과 부귀를 영원히 그의 자손에게 대물림하려는 자, 그래서 민족과 국가란 공동체를 부단히 유지해야만 하는 자, 따라서 민족과 국가란 공동체의 당위성과 개인의 가치를 초월하는 그 존엄성을 끝도 없이 창조하고 되뇌어야 하는 자, 종국에는 민족과 국가란 공동체에 속해 있다고 태내에서부터 세뇌된 모든 이들의 삶과 행동에서 영원히 자기복제되는 순환의 고리, 영생하는 애국의 원동력은 그 순환의 골에서 온다.\n",
            "엽기적인 살인사건이 발생한 장소를 관광하는 투어팀. 그 팀에서 관광객들은 살인사건과 관련하여 히스테리컬한 반응을 보이는데 과연 이들의 정체는? (Tourists see whrer a murder take place. They respond hysterically to the murder…what are they?)\n",
            " 제46회 발라돌리드 국제영화제 (2001, 스페인)\n",
            "착하지만 엉뚱한 태희(배두나 분), 예쁜 깍쟁이 혜주(이요원 분), 그림을 잘 그리는 지영(옥지영 분), 명랑한 쌍둥이 비류(이은실 분)와 온조(이은주 분)는 단짝친구들. 늘 함께였던 그들이지만 스무 살이 되면서 길이 달라진다. 증권회사에 입사한 혜주는 성공한 커리어우먼의 야심을 키우고 미술에 재능이 있는 지영은 유학을 꿈꾼다. 한편 태희는 봉사활동에서 알게 된 뇌성마비 시인을 좋아하는데...\n",
            "  어느 날 지영이 길 잃은 새끼 고양이 티티를 만남면서 스무 살 그녀들의 삶에 고양이 한 마리가 끼어들게 된다. 혼자 있길 좋아하고, 쉽게 마음을 열지 않는 신비로운 동물 고양이. 고양이를 닮은 스무 살 그녀들. 고양이 티티와 함께 한 시간동안 삶은 예상못한 방향으로 흘러가지만 마침내 그녀들만의 해결책을 찾게 되는데... 사랑스런 몽상가 태희, 아름다운 야심가 혜주, 신비로운 아웃사이더 지영. 마지막으로 고양이를 부탁받은 사람은 누구일까?\n",
            "인도 등 아시아 식민지에 처음 발을 디딘 뒤 여행하고 “경영”한 이들은 과연 누구였을까? 과거의 이미지들은, 이민과 인종 문제, ‘오리엔탈리즘’이 격렬히 충돌하고 있는 현재와 강력하게 공명한다.\n",
            " [제19회 인디다큐페스티발]\n",
            "홀로 살아가는 미국 할머니와 한국 할머니의 이야기. 공원에서 가끔 마주치게 되는 그들은 비록 언어 소통의 어려움을 겪지만 시간이 흘러감에 따라 서로 가까워져 그들의 외로움과 우정을 공유하게 된다. 겨울이 지나고 봄이 왔을 때 길가의 민들레 홀씨는 삶의 이치를 말해주듯 한 할머니의 주위를 맴돈다. (Two elderly widows, an American and a Korean, frequent the same park in Philadelphia and attempt a friendship, though the Korean widow speaks no English. Driven by loneliness and a spark of hope, they persevere within the limits of body language, and the outcome poses a question of life as fundamental as a flower.)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 약 15분정도 걸립니다.\n",
        "from konlpy.tag import Okt\n",
        "okt = Okt()\n",
        "tokenized = []\n",
        "with open(base_path+'synopsis.txt', 'r') as file:\n",
        "    while True:\n",
        "        line = file.readline()\n",
        "        if not line: break\n",
        "        words = okt.pos(line, stem=True, norm=True)\n",
        "        res = []\n",
        "        for w in words:\n",
        "            if w[1] in [\"Noun\"]:      # \"Adjective\", \"Verb\" 등을 포함할 수도 있습니다.\n",
        "                res.append(w[0])    # 명사일 때만 tokenized 에 저장하게 됩니다. \n",
        "        tokenized.append(res)"
      ],
      "metadata": {
        "id": "BpY7mWbYexmj"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(len(tokenized))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hxpFN8CWe40c",
        "outputId": "40c7e51a-c95f-48e3-b0a2-67d4c38d5a13"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "71156\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 3. 추출된 결과로 embedding model 만들기"
      ],
      "metadata": {
        "id": "QaXk2kSIY2rN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from gensim.models import Word2Vec\n",
        "\n",
        "# tokenized에 담긴 데이터를 가지고 나만의 Word2Vec을 생성합니다.\n",
        "# Gensim 3.X 에서는 아래와 같이 생성합니다. \n",
        "model = Word2Vec(tokenized, size=100, window=5, min_count=3, sg=0)  \n",
        "model.most_similar(positive=['영화'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KkVAyQaAfA8H",
        "outputId": "84678925-1ce3-4361-fec7-8d6a7194c7d5"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: DeprecationWarning: Call to deprecated `most_similar` (Method will be removed in 4.0.0, use self.wv.most_similar() instead).\n",
            "  \n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[('작품', 0.9138615727424622),\n",
              " ('다큐멘터리', 0.859940767288208),\n",
              " ('드라마', 0.8240671157836914),\n",
              " ('영화로', 0.8227626085281372),\n",
              " ('에마데딘', 0.8106018900871277),\n",
              " ('주제', 0.8017955422401428),\n",
              " ('형식', 0.7993396520614624),\n",
              " ('행위예술', 0.7951189279556274),\n",
              " ('코미디', 0.7939667701721191),\n",
              " ('스토리', 0.7826871871948242)]"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.wv.most_similar(positive=['액션'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8Zg83WU6fJKO",
        "outputId": "511e1fc5-3d2a-447c-cbac-7f6e33898f63"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[('퍼포먼스', 0.9056079387664795),\n",
              " ('참여', 0.9054061770439148),\n",
              " ('리얼', 0.8977599740028381),\n",
              " ('호러', 0.8975878357887268),\n",
              " ('블록버스터', 0.8928160071372986),\n",
              " ('각', 0.8910235166549683),\n",
              " ('대작', 0.8886705636978149),\n",
              " ('구성', 0.8881487846374512),\n",
              " ('흥미진진', 0.8875563144683838),\n",
              " ('비쥬', 0.8852801322937012)]"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 4. target, attribute 단어 셋 만들기\n",
        "이전 스텝에서는 TF-IDF를 사용해서 단어 셋을 만들었습니다. 이 방법으로도 어느 정도는 대표 단어를 잘 선정할 수 있습니다. 그러나 TF-IDF가 높은 단어를 골랐음에도 불구하고 중복되는 단어가 발생하는 문제가 있었습니다. 개념축을 표현하는 단어가 제대로 선정되지 않은 것은 WEAT 계산 결과에 악영향을 미칩니다.\n",
        "\n",
        "TF-IDF를 적용했을 때의 문제점이 무엇인지 지적 가능하다면 그 문제점을 지적하고 스스로 방법을 개선하여 대표 단어 셋을 구축해 보기 바랍니다. TF-IDF 방식을 쓰더라도 중복된 단어를 잘 제거하면 여전히 유용한 방식이 될 수 있습니다."
      ],
      "metadata": {
        "id": "bYoIT5V3Y54e"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "art_txt = 'synopsis_art.txt'\n",
        "gen_txt = 'synopsis_gen.txt'\n",
        "\n",
        "def read_token(file_name):\n",
        "    okt = Okt()\n",
        "    result = []\n",
        "    with open(base_path + file_name, 'r') as fread: \n",
        "        print(file_name, '파일을 읽고 있습니다.')\n",
        "        while True:\n",
        "            line = fread.readline() \n",
        "            if not line: break \n",
        "            tokenlist = okt.pos(line, stem=True, norm=True) \n",
        "            for word in tokenlist:\n",
        "                if word[1] in [\"Noun\"]:#, \"Adjective\", \"Verb\"]:\n",
        "                    result.append((word[0])) \n",
        "    return ' '.join(result)"
      ],
      "metadata": {
        "id": "z2WwYZgif-JN"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "art = read_token(art_txt)\n",
        "gen = read_token(gen_txt)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cKOXmcaqgJbS",
        "outputId": "2c5f3c8d-5e6c-4608-e75f-9182b68b15f8"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "synopsis_art.txt 파일을 읽고 있습니다.\n",
            "synopsis_gen.txt 파일을 읽고 있습니다.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "vectorizer = TfidfVectorizer()\n",
        "X = vectorizer.fit_transform([art, gen])"
      ],
      "metadata": {
        "id": "Z6WygwM4gQuX"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(vectorizer.vocabulary_['영화'])\n",
        "print(vectorizer.get_feature_names()[23976])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TCtTh1OTgSSJ",
        "outputId": "daf8c6b7-4757-4a25-c8a8-4bdef67d8d69"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "23976\n",
            "영화\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function get_feature_names is deprecated; get_feature_names is deprecated in 1.0 and will be removed in 1.2. Please use get_feature_names_out instead.\n",
            "  warnings.warn(msg, category=FutureWarning)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m1 = X[0].tocoo()   # art를 TF-IDF로 표현한 spart matrix를 가져옵니다. \n",
        "m2 = X[1].tocoo()   # gen을 TF-IDF로 표현한 spart matrix를 가져옵니다. \n",
        "\n",
        "w1 = [[i, j] for i, j in zip(m1.col, m1.data)]\n",
        "w2 = [[i, j] for i, j in zip(m2.col, m2.data)]\n",
        "\n",
        "w1.sort(key=lambda x: x[1], reverse=True)   #art를 구성하는 단어들을 TF-IDF가 높은 순으로 정렬합니다. \n",
        "w2.sort(key=lambda x: x[1], reverse=True)   #gen을 구성하는 단어들을 TF-IDF가 높은 순으로 정렬합니다. \n",
        "\n",
        "print('예술영화를 대표하는 단어들:')\n",
        "for i in range(100):\n",
        "    print(vectorizer.get_feature_names()[w1[i][0]], end=', ')\n",
        "\n",
        "print('\\n')\n",
        "    \n",
        "print('일반영화를 대표하는 단어들:')\n",
        "for i in range(100):\n",
        "    print(vectorizer.get_feature_names()[w2[i][0]], end=', ')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IEk2li7rgXlG",
        "outputId": "6ada5e0a-46a2-4696-cae0-700631ed3e07"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "예술영화를 대표하는 단어들:\n",
            "그녀, 자신, 시작, 위해, 사랑, 사람, 영화, 친구, 남자, 가족, 이야기, 마을, 사건, 마음, 세상, 아버지, 아이, 엄마, 모든, 여자, 대한, 서로, 과연, 다시, 시간, 아들, 소녀, 아내, 다른, 사이, 영화제, 세계, 사실, 하나, 점점, 남편, 감독, 여행, 인생, 발견, 모두, 순간, 우리, 가장, 마지막, 생활, 아빠, 모습, 통해, 죽음, 기억, 비밀, 학교, 음악, 한편, 소년, 생각, 도시, 명의, 사고, 결혼, 전쟁, 때문, 위기, 이제, 최고, 이자, 과거, 일상, 경찰, 상황, 간다, 미국, 결심, 운명, 현실, 관계, 지금, 단편, 여인, 하루, 이름, 이후, 준비, 인간, 감정, 만난, 국제, 처음, 충격, 살인, 누구, 동안, 존재, 그린, 어머니, 연인, 계속, 동생, 작품, \n",
            "\n",
            "일반영화를 대표하는 단어들:\n",
            "자신, 그녀, 영화제, 위해, 사람, 시작, 국제, 영화, 친구, 사랑, 남자, 이야기, 대한, 서울, 여자, 사건, 남편, 아이, 가족, 아버지, 다른, 마을, 시간, 엄마, 아들, 모든, 단편, 마음, 사실, 다시, 세계, 모습, 작품, 통해, 생각, 서로, 세상, 발견, 감독, 아내, 관계, 소녀, 사이, 하나, 우리, 애니메이션, 때문, 여성, 죽음, 과연, 점점, 인간, 생활, 한편, 결혼, 상황, 모두, 기억, 명의, 소년, 여행, 가장, 간다, 순간, 이제, 도시, 비밀, 학교, 과거, 가지, 이자, 경찰, 마지막, 미국, 동안, 전쟁, 주인공, 대해, 존재, 현실, 연출, 사고, 살인, 일상, 어머니, 계속, 사회, 인생, 다큐멘터리, 부문, 섹스, 최고, 바로, 동생, 의도, 하루, 위기, 계획, 정체, 한국, "
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "두 개념을 대표하는 단어를 TF-IDF가 높은 순으로 추출하고 싶었는데, 양쪽에 중복된 단어가 너무 많은 것을 볼 수 있습니다. 두 개념축이 대조되도록 대표하는 단어 셋을 만들고 싶기 때문에 단어가 서로 중복되지 않게 단어셋을 추출해야 합니다. 우선 상위 100개의 단어들 중 중복되는 단어를 제외하고 상위 n(=15)개의 단어를 추출합니다."
      ],
      "metadata": {
        "id": "gj_mMNKppzA5"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "n = 15\n",
        "w1_, w2_ = [], []\n",
        "for i in range(100):\n",
        "    w1_.append(vectorizer.get_feature_names()[w1[i][0]])\n",
        "    w2_.append(vectorizer.get_feature_names()[w2[i][0]])\n",
        "\n",
        "# w1에만 있고 w2에는 없는, 예술영화를 잘 대표하는 단어를 15개 추출한다.\n",
        "target_art, target_gen = [], []\n",
        "for i in range(100):\n",
        "    if (w1_[i] not in w2_) and (w1_[i] in model.wv): target_art.append(w1_[i])\n",
        "    if len(target_art) == n: break \n",
        "\n",
        "# w2에만 있고 w1에는 없는, 일반영화를 잘 대표하는 단어를 15개 추출한다.\n",
        "for i in range(100):\n",
        "    if (w2_[i] not in w1_) and (w2_[i] in model.wv): target_gen.append(w2_[i])\n",
        "    if len(target_gen) == n: break"
      ],
      "metadata": {
        "id": "ywS8jOEep0Kj"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(target_art)\n",
        "print(target_gen)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "40-JfUHMp1eE",
        "outputId": "054ab6d3-b4df-429d-b382-735668e27512"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['아빠', '음악', '결심', '운명', '지금', '여인', '이름', '이후', '준비', '감정', '만난', '처음', '충격', '누구', '그린']\n",
            "['서울', '애니메이션', '여성', '가지', '주인공', '대해', '연출', '사회', '다큐멘터리', '부문', '섹스', '바로', '의도', '계획', '정체']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "genre_txt = ['synopsis_SF.txt', 'synopsis_family.txt', 'synopsis_show.txt', 'synopsis_horror.txt', 'synopsis_etc.txt', \n",
        "             'synopsis_documentary.txt', 'synopsis_drama.txt', 'synopsis_romance.txt', 'synopsis_musical.txt', \n",
        "             'synopsis_mystery.txt', 'synopsis_crime.txt', 'synopsis_historical.txt', 'synopsis_western.txt', \n",
        "             'synopsis_adult.txt', 'synopsis_thriller.txt', 'synopsis_animation.txt', 'synopsis_action.txt', \n",
        "             'synopsis_adventure.txt', 'synopsis_war.txt', 'synopsis_comedy.txt', 'synopsis_fantasy.txt']\n",
        "genre_name = ['SF', '가족', '공연', '공포(호러)', '기타', '다큐멘터리', '드라마', '멜로로맨스', '뮤지컬', '미스터리', '범죄', '사극', '서부극(웨스턴)',\n",
        "         '성인물(에로)', '스릴러', '애니메이션', '액션', '어드벤처', '전쟁', '코미디', '판타지']"
      ],
      "metadata": {
        "id": "PL5YJ-sup4Ks"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# 약 10분정도 걸립니다.\n",
        "genre = []\n",
        "for file_name in genre_txt:\n",
        "    genre.append(read_token(file_name))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tkD3SwwTp5RV",
        "outputId": "76497094-1ace-46e8-ac77-1a0594f9c13a"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "synopsis_SF.txt 파일을 읽고 있습니다.\n",
            "synopsis_family.txt 파일을 읽고 있습니다.\n",
            "synopsis_show.txt 파일을 읽고 있습니다.\n",
            "synopsis_horror.txt 파일을 읽고 있습니다.\n",
            "synopsis_etc.txt 파일을 읽고 있습니다.\n",
            "synopsis_documentary.txt 파일을 읽고 있습니다.\n",
            "synopsis_drama.txt 파일을 읽고 있습니다.\n",
            "synopsis_romance.txt 파일을 읽고 있습니다.\n",
            "synopsis_musical.txt 파일을 읽고 있습니다.\n",
            "synopsis_mystery.txt 파일을 읽고 있습니다.\n",
            "synopsis_crime.txt 파일을 읽고 있습니다.\n",
            "synopsis_historical.txt 파일을 읽고 있습니다.\n",
            "synopsis_western.txt 파일을 읽고 있습니다.\n",
            "synopsis_adult.txt 파일을 읽고 있습니다.\n",
            "synopsis_thriller.txt 파일을 읽고 있습니다.\n",
            "synopsis_animation.txt 파일을 읽고 있습니다.\n",
            "synopsis_action.txt 파일을 읽고 있습니다.\n",
            "synopsis_adventure.txt 파일을 읽고 있습니다.\n",
            "synopsis_war.txt 파일을 읽고 있습니다.\n",
            "synopsis_comedy.txt 파일을 읽고 있습니다.\n",
            "synopsis_fantasy.txt 파일을 읽고 있습니다.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "vectorizer = TfidfVectorizer()\n",
        "X = vectorizer.fit_transform(genre)\n",
        "\n",
        "print(X.shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AiARN9Lgp6jO",
        "outputId": "802cfdd2-6558-449b-c2c9-63581431fbf9"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(21, 42191)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m = [X[i].tocoo() for i in range(X.shape[0])]\n",
        "\n",
        "w = [[[i, j] for i, j in zip(mm.col, mm.data)] for mm in m]\n",
        "\n",
        "for i in range(len(w)):\n",
        "    w[i].sort(key=lambda x: x[1], reverse=True)\n",
        "attributes = []\n",
        "for i in range(len(w)):\n",
        "    print(genre_name[i], end=': ')\n",
        "    attr = []\n",
        "    j = 0\n",
        "    while (len(attr) < 15):\n",
        "        if vectorizer.get_feature_names()[w[i][j][0]] in model.wv:\n",
        "            attr.append(vectorizer.get_feature_names()[w[i][j][0]])\n",
        "            print(vectorizer.get_feature_names()[w[i][j][0]], end=', ')\n",
        "        j += 1\n",
        "    attributes.append(attr)\n",
        "    print()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "p2sgMJCqp7zE",
        "outputId": "de5c9d14-466d-40fc-8bb7-393f9d0416bf"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "SF: 위해, 자신, 지구, 시작, 사람, 인류, 인간, 미래, 우주, 그녀, 로봇, 세계, 모든, 박사, 우주선, \n",
            "가족: 엄마, 아빠, 가족, 영화제, 자신, 위해, 친구, 아주르, 아버지, 시작, 그녀, 아들, 마을, 국제, 낙타, \n",
            "공연: 오페라, 사랑, 토스카, 실황, 올레, 자신, 카바, 그녀, 공연, 오텔로, 리골레토, 백작, 프레, 베르디, 위해, \n",
            "공포(호러): 시작, 위해, 사람, 자신, 친구, 그녀, 사건, 공포, 발견, 죽음, 마을, 가족, 악령, 남자, 좀비, \n",
            "기타: 영화제, 국제, 서울, 단편, 영화, 자신, 사람, 이야기, 그녀, 남자, 위해, 시작, 사랑, 뉴미디어, 페스티벌, \n",
            "다큐멘터리: 영화제, 영화, 다큐, 국제, 다큐멘터리, 사람, 이야기, 대한, 자신, 감독, 위해, 서울, 우리, 시작, 세계, \n",
            "드라마: 자신, 영화제, 그녀, 사람, 사랑, 영화, 위해, 시작, 국제, 남자, 친구, 이야기, 엄마, 여자, 아버지, \n",
            "멜로로맨스: 그녀, 사랑, 자신, 시작, 남편, 남자, 여자, 사람, 친구, 섹스, 위해, 마음, 결혼, 서로, 아내, \n",
            "뮤지컬: 뮤지컬, 사랑, 에스메랄다, 그녀, 음악, 충무로, 모차르트, 영화, 토스카, 자신, 니웨, 카바, 영화제, 바흐, 페뷔스, \n",
            "미스터리: 사건, 그녀, 시작, 자신, 위해, 사람, 발견, 사고, 진실, 죽음, 기억, 살인, 친구, 아내, 남자, \n",
            "범죄: 사건, 위해, 자신, 경찰, 시작, 그녀, 범죄, 조직, 살인, 사람, 마약, 형사, 남자, 모든, 살해, \n",
            "사극: 조선, 위해, 시작, 신기전, 사랑, 자신, 아가멤논, 황제, 그녀, 루안, 최고, 운명, 사람, 하선, 전쟁, \n",
            "서부극(웨스턴): 서부, 보안관, 위해, 벌린, 카우보이, 그레이프바인, 헨리, 마을, 자신, 개릿, 아이, 시작, 무법자, 프린트, 마적, \n",
            "성인물(에로): 그녀, 남편, 마사지, 자신, 섹스, 관계, 영화, 정사, 남자, 위해, 시작, 여자, 유부녀, 마음, 사랑, \n",
            "스릴러: 자신, 그녀, 사건, 시작, 위해, 사람, 살인, 남자, 발견, 아내, 경찰, 친구, 모든, 사실, 살해, \n",
            "애니메이션: 애니메이션, 국제, 영화제, 친구, 인디애니페스트, 위해, 자신, 시작, 사람, 페스티벌, 서울, 이야기, 아이, 마을, 소녀, \n",
            "액션: 위해, 자신, 시작, 조직, 사건, 사람, 그녀, 경찰, 전쟁, 모든, 목숨, 사실, 친구, 가족, 요원, \n",
            "어드벤처: 위해, 자신, 시작, 친구, 마을, 아버지, 영화, 아이, 사람, 여행, 세계, 앤트, 세상, 가족, 모험, \n",
            "전쟁: 전쟁, 독일군, 전투, 위해, 작전, 시작, 부대, 윈터스, 독일, 연합군, 미군, 임무, 자신, 사람, 나치, \n",
            "코미디: 그녀, 자신, 시작, 위해, 사랑, 사람, 친구, 영화, 남자, 여자, 영화제, 가족, 과연, 마을, 사건, \n",
            "판타지: 자신, 그녀, 시작, 위해, 사람, 사랑, 요괴, 영화제, 이야기, 영화, 소녀, 남자, 인간, 세상, 마을, \n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 5. WEAT score 계산과 시각화\n",
        "\n",
        "영화 구분, 영화 장르에 따른 편향성을 측정하여 WEAT score로 계산해 보고 이를 Heatmap 형태로 시각화해 봅시다. 편향성이 두드러지는 영화장르 attribute 구성에는 어떤 케이스가 있는지 시각적으로 두드러지게 구성되면 좋습니다."
      ],
      "metadata": {
        "id": "2oCpoERpZIUb"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "id": "fPiDjtQ2c3F1",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4be91059-aa42-4868-ef91-6f4d06968b4c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "슝~\n"
          ]
        }
      ],
      "source": [
        "matrix = [[0 for _ in range(len(genre_name))] for _ in range(len(genre_name))]\n",
        "print(\"슝~\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def cos_sim(i, j):\n",
        "  return dot(i, j.T)/(norm(i)*norm(j))\n",
        "\n",
        "def s(w, A,B):\n",
        "  c_a = cos_sim(w,A)\n",
        "  c_b = cos_sim(w, B)\n",
        "  mean_A = np.mean(c_a, axis=-1)\n",
        "  mean_B = np.mean(c_b, axis=-1)\n",
        "  return mean_A - mean_B\n",
        "  \n",
        "def weat_score(X,Y,A,B):\n",
        "  s_X = s(X,A,B)\n",
        "  s_Y = s(Y,A,B)\n",
        "\n",
        "  mean_X = np.mean(s_X)\n",
        "  mean_Y = np.mean(s_Y)\n",
        "  \n",
        "  std_dev = np.std(np.concatenate([s_X,s_Y],axis=0))\n",
        "\n",
        "  return (mean_X-mean_Y)/std_dev"
      ],
      "metadata": {
        "id": "RqFdRE9qGZWA"
      },
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "A = np.array([model.wv[word] for word in target_art])\n",
        "B = np.array([model.wv[word] for word in target_gen])\n",
        "\n",
        "for i in range(len(genre_name)-1):\n",
        "    for j in range(i+1, len(genre_name)):\n",
        "        X = np.array([model.wv[word] for word in attributes[i]])\n",
        "        Y = np.array([model.wv[word] for word in attributes[j]])\n",
        "        matrix[i][j] = weat_score(X, Y, A, B)"
      ],
      "metadata": {
        "id": "mmf4T3LJEAYJ"
      },
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "for i in range(len(genre_name)-1):\n",
        "    for j in range(i+1, len(genre_name)):\n",
        "        print(genre_name[i], '/', genre_name[j],' : ',matrix[i][j])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hTowenjFazWf",
        "outputId": "0e53cf86-a763-4d6b-b08c-3daf13a02713"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "SF / 가족  :  -0.3382175\n",
            "SF / 공연  :  -0.28504646\n",
            "SF / 공포(호러)  :  -0.79368377\n",
            "SF / 기타  :  0.3489284\n",
            "SF / 다큐멘터리  :  0.6942957\n",
            "SF / 드라마  :  -0.2567333\n",
            "SF / 멜로로맨스  :  -1.315048\n",
            "SF / 뮤지컬  :  0.33875138\n",
            "SF / 미스터리  :  -0.9921432\n",
            "SF / 범죄  :  -0.38545704\n",
            "SF / 사극  :  -0.5222725\n",
            "SF / 서부극(웨스턴)  :  -0.38846233\n",
            "SF / 성인물(에로)  :  -0.8891135\n",
            "SF / 스릴러  :  -0.8006997\n",
            "SF / 애니메이션  :  0.32418212\n",
            "SF / 액션  :  -0.47639066\n",
            "SF / 어드벤처  :  -0.52191675\n",
            "SF / 전쟁  :  0.15884635\n",
            "SF / 코미디  :  -0.33223748\n",
            "SF / 판타지  :  -0.1274497\n",
            "가족 / 공연  :  0.09055676\n",
            "가족 / 공포(호러)  :  -0.20696914\n",
            "가족 / 기타  :  0.54464096\n",
            "가족 / 다큐멘터리  :  0.7994086\n",
            "가족 / 드라마  :  0.07324919\n",
            "가족 / 멜로로맨스  :  -0.6172583\n",
            "가족 / 뮤지컬  :  0.53100646\n",
            "가족 / 미스터리  :  -0.3441183\n",
            "가족 / 범죄  :  0.09332161\n",
            "가족 / 사극  :  -0.055975523\n",
            "가족 / 서부극(웨스턴)  :  0.08060718\n",
            "가족 / 성인물(에로)  :  -0.31884396\n",
            "가족 / 스릴러  :  -0.20695114\n",
            "가족 / 애니메이션  :  0.5268589\n",
            "가족 / 액션  :  0.021781942\n",
            "가족 / 어드벤처  :  -0.035680257\n",
            "가족 / 전쟁  :  0.44304118\n",
            "가족 / 코미디  :  0.040839806\n",
            "가족 / 판타지  :  0.19940251\n",
            "공연 / 공포(호러)  :  -0.372706\n",
            "공연 / 기타  :  0.52016145\n",
            "공연 / 다큐멘터리  :  0.81593764\n",
            "공연 / 드라마  :  -0.010343365\n",
            "공연 / 멜로로맨스  :  -0.8608492\n",
            "공연 / 뮤지컬  :  0.5035786\n",
            "공연 / 미스터리  :  -0.5411168\n",
            "공연 / 범죄  :  -0.012739869\n",
            "공연 / 사극  :  -0.17875789\n",
            "공연 / 서부극(웨스턴)  :  -0.02595595\n",
            "공연 / 성인물(에로)  :  -0.4933916\n",
            "공연 / 스릴러  :  -0.37422994\n",
            "공연 / 애니메이션  :  0.5003909\n",
            "공연 / 액션  :  -0.097443\n",
            "공연 / 어드벤처  :  -0.16010652\n",
            "공연 / 전쟁  :  0.41114137\n",
            "공연 / 코미디  :  -0.05387902\n",
            "공연 / 판타지  :  0.12736686\n",
            "공포(호러) / 기타  :  0.85083187\n",
            "공포(호러) / 다큐멘터리  :  1.1868268\n",
            "공포(호러) / 드라마  :  0.30435455\n",
            "공포(호러) / 멜로로맨스  :  -0.797134\n",
            "공포(호러) / 뮤지컬  :  0.80791605\n",
            "공포(호러) / 미스터리  :  -0.2468708\n",
            "공포(호러) / 범죄  :  0.49006787\n",
            "공포(호러) / 사극  :  0.2061236\n",
            "공포(호러) / 서부극(웨스턴)  :  0.45318922\n",
            "공포(호러) / 성인물(에로)  :  -0.19708367\n",
            "공포(호러) / 스릴러  :  0.001969908\n",
            "공포(호러) / 애니메이션  :  0.8363622\n",
            "공포(호러) / 액션  :  0.36899704\n",
            "공포(호러) / 어드벤처  :  0.25413528\n",
            "공포(호러) / 전쟁  :  0.92874354\n",
            "공포(호러) / 코미디  :  0.2925212\n",
            "공포(호러) / 판타지  :  0.49444252\n",
            "기타 / 다큐멘터리  :  0.24397759\n",
            "기타 / 드라마  :  -0.4848895\n",
            "기타 / 멜로로맨스  :  -1.1648632\n",
            "기타 / 뮤지컬  :  0.01188994\n",
            "기타 / 미스터리  :  -0.9663598\n",
            "기타 / 범죄  :  -0.60014266\n",
            "기타 / 사극  :  -0.68700707\n",
            "기타 / 서부극(웨스턴)  :  -0.6013844\n",
            "기타 / 성인물(에로)  :  -0.9201145\n",
            "기타 / 스릴러  :  -0.85372967\n",
            "기타 / 애니메이션  :  -0.024216807\n",
            "기타 / 액션  :  -0.6562487\n",
            "기타 / 어드벤처  :  -0.68603766\n",
            "기타 / 전쟁  :  -0.24341954\n",
            "기타 / 코미디  :  -0.55032724\n",
            "기타 / 판타지  :  -0.4003621\n",
            "다큐멘터리 / 드라마  :  -0.74615264\n",
            "다큐멘터리 / 멜로로맨스  :  -1.4676421\n",
            "다큐멘터리 / 뮤지컬  :  -0.21719946\n",
            "다큐멘터리 / 미스터리  :  -1.2973684\n",
            "다큐멘터리 / 범죄  :  -0.9576978\n",
            "다큐멘터리 / 사극  :  -1.0033106\n",
            "다큐멘터리 / 서부극(웨스턴)  :  -0.95033187\n",
            "다큐멘터리 / 성인물(에로)  :  -1.2316886\n",
            "다큐멘터리 / 스릴러  :  -1.1920847\n",
            "다큐멘터리 / 애니메이션  :  -0.27243167\n",
            "다큐멘터리 / 액션  :  -1.0047735\n",
            "다큐멘터리 / 어드벤처  :  -1.015901\n",
            "다큐멘터리 / 전쟁  :  -0.5865653\n",
            "다큐멘터리 / 코미디  :  -0.83430326\n",
            "다큐멘터리 / 판타지  :  -0.68567795\n",
            "드라마 / 멜로로맨스  :  -0.71621275\n",
            "드라마 / 뮤지컬  :  0.47343343\n",
            "드라마 / 미스터리  :  -0.44424632\n",
            "드라마 / 범죄  :  0.0011276416\n",
            "드라마 / 사극  :  -0.14449498\n",
            "드라마 / 서부극(웨스턴)  :  -0.010409527\n",
            "드라마 / 성인물(에로)  :  -0.41323727\n",
            "드라마 / 스릴러  :  -0.30489644\n",
            "드라마 / 애니메이션  :  0.46601126\n",
            "드라마 / 액션  :  -0.071123466\n",
            "드라마 / 어드벤처  :  -0.12655418\n",
            "드라마 / 전쟁  :  0.36568046\n",
            "드라마 / 코미디  :  -0.03811147\n",
            "드라마 / 판타지  :  0.124056526\n",
            "멜로로맨스 / 뮤지컬  :  1.1049484\n",
            "멜로로맨스 / 미스터리  :  0.64598584\n",
            "멜로로맨스 / 범죄  :  1.1733886\n",
            "멜로로맨스 / 사극  :  0.8084712\n",
            "멜로로맨스 / 서부극(웨스턴)  :  1.1103057\n",
            "멜로로맨스 / 성인물(에로)  :  0.51768476\n",
            "멜로로맨스 / 스릴러  :  0.8163842\n",
            "멜로로맨스 / 애니메이션  :  1.1580111\n",
            "멜로로맨스 / 액션  :  1.0616796\n",
            "멜로로맨스 / 어드벤처  :  0.9005683\n",
            "멜로로맨스 / 전쟁  :  1.4058793\n",
            "멜로로맨스 / 코미디  :  0.76386577\n",
            "멜로로맨스 / 판타지  :  0.9316772\n",
            "뮤지컬 / 미스터리  :  -0.91580856\n",
            "뮤지컬 / 범죄  :  -0.5718645\n",
            "뮤지컬 / 사극  :  -0.65812945\n",
            "뮤지컬 / 서부극(웨스턴)  :  -0.5740112\n",
            "뮤지컬 / 성인물(에로)  :  -0.87661505\n",
            "뮤지컬 / 스릴러  :  -0.8102061\n",
            "뮤지컬 / 애니메이션  :  -0.035003696\n",
            "뮤지컬 / 액션  :  -0.62516433\n",
            "뮤지컬 / 어드벤처  :  -0.65538687\n",
            "뮤지컬 / 전쟁  :  -0.24045855\n",
            "뮤지컬 / 코미디  :  -0.5333221\n",
            "뮤지컬 / 판타지  :  -0.39116168\n",
            "미스터리 / 범죄  :  0.7346337\n",
            "미스터리 / 사극  :  0.40685043\n",
            "미스터리 / 서부극(웨스턴)  :  0.68582374\n",
            "미스터리 / 성인물(에로)  :  0.013376242\n",
            "미스터리 / 스릴러  :  0.25374615\n",
            "미스터리 / 애니메이션  :  0.9546034\n",
            "미스터리 / 액션  :  0.6090997\n",
            "미스터리 / 어드벤처  :  0.47178707\n",
            "미스터리 / 전쟁  :  1.1153954\n",
            "미스터리 / 코미디  :  0.45256844\n",
            "미스터리 / 판타지  :  0.6482719\n",
            "범죄 / 사극  :  -0.21188682\n",
            "범죄 / 서부극(웨스턴)  :  -0.018018853\n",
            "범죄 / 성인물(에로)  :  -0.6298272\n",
            "범죄 / 스릴러  :  -0.49528176\n",
            "범죄 / 애니메이션  :  0.57991403\n",
            "범죄 / 액션  :  -0.114125624\n",
            "범죄 / 어드벤처  :  -0.1924853\n",
            "범죄 / 전쟁  :  0.54620427\n",
            "범죄 / 코미디  :  -0.05199083\n",
            "범죄 / 판타지  :  0.16284162\n",
            "사극 / 서부극(웨스턴)  :  0.1904529\n",
            "사극 / 성인물(에로)  :  -0.35617667\n",
            "사극 / 스릴러  :  -0.2067197\n",
            "사극 / 애니메이션  :  0.66951776\n",
            "사극 / 액션  :  0.11173949\n",
            "사극 / 어드벤처  :  0.029395262\n",
            "사극 / 전쟁  :  0.65498984\n",
            "사극 / 코미디  :  0.11340257\n",
            "사극 / 판타지  :  0.30607376\n",
            "서부극(웨스턴) / 성인물(에로)  :  -0.5933336\n",
            "서부극(웨스턴) / 스릴러  :  -0.4574399\n",
            "서부극(웨스턴) / 애니메이션  :  0.58140314\n",
            "서부극(웨스턴) / 액션  :  -0.09215883\n",
            "서부극(웨스턴) / 어드벤처  :  -0.1698917\n",
            "서부극(웨스턴) / 전쟁  :  0.5435436\n",
            "서부극(웨스턴) / 코미디  :  -0.038047332\n",
            "서부극(웨스턴) / 판타지  :  0.17222875\n",
            "성인물(에로) / 스릴러  :  0.20159084\n",
            "성인물(에로) / 애니메이션  :  0.90741646\n",
            "성인물(에로) / 액션  :  0.52078635\n",
            "성인물(에로) / 어드벤처  :  0.4083104\n",
            "성인물(에로) / 전쟁  :  1.0076001\n",
            "성인물(에로) / 코미디  :  0.41389433\n",
            "성인물(에로) / 판타지  :  0.6002241\n",
            "스릴러 / 애니메이션  :  0.8392993\n",
            "스릴러 / 액션  :  0.3723522\n",
            "스릴러 / 어드벤처  :  0.25551042\n",
            "스릴러 / 전쟁  :  0.9367848\n",
            "스릴러 / 코미디  :  0.29329136\n",
            "스릴러 / 판타지  :  0.496486\n",
            "애니메이션 / 액션  :  -0.6373973\n",
            "애니메이션 / 어드벤처  :  -0.66821235\n",
            "애니메이션 / 전쟁  :  -0.21677056\n",
            "애니메이션 / 코미디  :  -0.5314767\n",
            "애니메이션 / 판타지  :  -0.37916693\n",
            "액션 / 어드벤처  :  -0.08583193\n",
            "액션 / 전쟁  :  0.62913215\n",
            "액션 / 코미디  :  0.02963151\n",
            "액션 / 판타지  :  0.2399755\n",
            "어드벤처 / 전쟁  :  0.66226953\n",
            "어드벤처 / 코미디  :  0.09277153\n",
            "어드벤처 / 판타지  :  0.29294035\n",
            "전쟁 / 코미디  :  -0.45148462\n",
            "전쟁 / 판타지  :  -0.2500135\n",
            "코미디 / 판타지  :  0.17487511\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fig, ax = plt.subplots(figsize=(20,20))\n",
        "\n",
        "np.random.seed(0)\n",
        "\n",
        "# 한글 지원 폰트\n",
        "sns.set(font_scale=1)\n",
        "ax = sns.heatmap(matrix, xticklabels=genre_name, yticklabels=genre_name, annot=True,  cmap='RdYlGn_r')\n",
        "ax\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "6vSfMgvEpTs-",
        "outputId": "ab60c53e-babe-4d5a-a88c-a9e78bdfaa1c"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x1440 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 7. 회고\n",
        "- 어려웠던 점\n",
        "  - LMS와 크게 바뀐 것이 없었기 때문에 딱히 어려운 점은 없었다.\n",
        "- 발생한 오류\n",
        "  - 시각화를 할때 한국어가 깨져서 라이브러리를 다운로드하고 적용하여 이를 해결할 수 있었다.\n",
        "- 루브릭 기준을 맞추기 위한 시도\n",
        "  - 결과를 보았을때 의미상 바르게 나온 것을 확인할 수 있다.\n",
        "  - 중복을 제거하여 보다 더 정확한 target, attribute에 대표성있는 단어셋을 생성하였다.\n",
        "  - 시각화가 잘 되어 진행되었다. 한글이 깨져서 문제가 생겼었지만 패치를 따로 설치하여 해결하였다."
      ],
      "metadata": {
        "id": "goZBWE5HwOUg"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 루브릭\n",
        "\n",
        "1. 주어진 영화 코퍼스를 바탕으로 워드임베딩 모델을 정상적으로 만들었다.\n",
        "  - 워드임베딩의 most_similar() 메소드 결과가 의미상 바르게 나왔다.\n",
        "\n",
        "2. 영화 구분, 장르별로 target, attribute에 대한 대표성있는 단어 셋을 생성하였다.\n",
        "  - 타당한 방법론을 통해 중복이 잘 제거되고 개념축을 의미적으로 잘 대표하는 단어 셋이 만들어졌다.\n",
        "\n",
        "3. WEAT score 계산 및 시각화를 정상적으로 진행하였다.\n",
        "  - 전체 영화 장르별로 예술/일반 영화에 대한 편향성 WEAT score가 상식에 부합하는 수치로 얻어졌으며 이를 잘 시각화하였다."
      ],
      "metadata": {
        "id": "a1ovOzinbUCF"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "8ya_RPj1bbBG"
      },
      "execution_count": 26,
      "outputs": []
    }
  ]
}