台灣同性婚姻論述中的「同志」

前情提要

在上一篇的文章中，我發現下福盟和伴侶盟兩個語料中，「同志」和「同性戀」兩個詞使用頻率有明顯的不同情形，在下福盟中，兩個詞出現的頻率幾乎相同，「同性戀」出現1393次，「同志」出現1305次；而在伴侶盟的語料中，「同性戀」出現569次，而「同志」則出現153次，前者出現的次數是後者出現的 3.7 倍。（見下圖圖表）

所以…

我很好奇到底這兩個詞在兩個語料中是如何使用的？以及為什麼在伴侶盟這兩個詞出現的次數差距很大，但在下福盟語料裡卻次數差不多。我將利用 concordance 工具，來看語料中這兩個詞出現的脈絡究竟是什麼，觀察前面接什麼樣的動詞，後面接什麼樣的名詞…等。透過觀察一個詞出現的脈絡，也許可以看出一些端倪。

先按照例行公事，匯入語料，並轉換成nltk.text.Text()物件：

import nltk
import re
import jieba
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.font_manager import FontProperties

plt.rcParams['figure.figsize'] = [10, 5]
myfont = FontProperties(fname=r'/usr/local/lib/python3.7/site-packages/matplotlib/mpl-data/fonts/ttf/msj.ttf',size=14)
sns.set(font=myfont.get_name())

%matplotlib inline

pd.set_option('display.max_rows', 2000)

LGBTFAMILY_PATH = "line_sentence_lgbtfamily.txt"
LOVEFAMILY_PATH = "line_sentence_lovefamily.txt"

lgbtfamily_raw_text = ""
lovefamily_raw_text = ""

with open(LGBTFAMILY_PATH) as f:
    lgbtfamily_raw_text = f.read()

with open(LOVEFAMILY_PATH) as f:
    lovefamily_raw_text = f.read()
    
# 將文本拆成 list of words
lgbtfamily_word_list = [word for sentence in lgbtfamily_raw_text.split('\n') for word in sentence.split(' ')]
lovefamily_word_list = [word for sentence in lovefamily_raw_text.split('\n') for word in sentence.split(' ')]

# 轉換好後，丟入 nltk.text.Text
lovefamily_text = nltk.text.Text(lovefamily_word_list)
lgbtfamily_text = nltk.text.Text(lgbtfamily_word_list)

nltk 套件中有兩個關於 concordance 工具的方法：nltk.text.Text.concordance()和nltk.text.Text.concordance_list()，前者可以直接以字串印出美美的 concordance，後者則是會把結果回傳成list，可以用來進行其他轉換。

下面我將利用 nltk.text.Text.concordance_list() 方法，再把結果轉成pandas的DataFrame，方便呈現出來。讓我們先看一下 nltk.text.Text.concordance_list 方法的文件：

help(nltk.text.Text.concordance_list)

Help on function concordance_list in module nltk.text:

concordance_list(self, word, width=79, lines=25)
    Generate a concordance for ``word`` with the specified context window.
    Word matching is not case-sensitive.

    :param word: The target word
    :type word: str
    :param width: The width of each line, in characters (default=80)
    :type width: int
    :param lines: The number of lines to display (default=25)
    :type lines: int

    :seealso: ``ConcordanceIndex``

下福盟中的「同志」

lovefamily_tongzhi_c = lovefamily_text.concordance_list('同志', width=50, lines=10000)

lovefamily_tongzhi_df = pd.DataFrame({
    "left_context": [' '.join(line.left) for line in lovefamily_tongzhi_c],
    "query": '同志',
    "right_context": [' '.join(line.right) for line in lovefamily_tongzhi_c],
})

lovefamily_tongzhi_df

伴侶盟中的「同志」

lgbtfamily_tongzhi_c = lgbtfamily_text.concordance_list('同志', width=50, lines=10000)

lgbtfamily_tongzhi_df = pd.DataFrame({
    "left_context": [' '.join(line.left) for line in lgbtfamily_tongzhi_c],
    "query": '同志',
    "right_context": [' '.join(line.right) for line in lgbtfamily_tongzhi_c],
})

lgbtfamily_tongzhi_df