88 lines
2.6 KiB
Python
88 lines
2.6 KiB
Python
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# http://www.ulliwaltinger.de/sentiment/
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# https://github.com/solariz/german_stopwords
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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import nltk
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import copy
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import encodings
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import csv
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from siteobj import *
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from nltk.corpus import treebank
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negatives = dict()
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positives = dict()
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neutrals = dict()
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with open("./reader/GermanPolarityClues-2012/GermanPolarityClues-Negative.tsv", "r", encoding="utf-8") as tsvfile:
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reader = csv.reader(tsvfile, delimiter='\t')
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for row in reader:
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if "-" not in row[4].split("/"):
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negatives[row[0]] = [float(row[4].split("/")[0]), float(row[4].split("/")[1]), float(row[4].split("/")[2])]
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with open("./reader/GermanPolarityClues-2012/GermanPolarityClues-Neutral.tsv", "r", encoding="utf-8") as tsvfile:
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reader = csv.reader(tsvfile, delimiter='\t')
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for row in reader:
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if "-" not in row[4].split("/"):
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neutrals[row[0]] = [float(row[4].split("/")[0]), float(row[4].split("/")[1]), float(row[4].split("/")[2])]
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with open("./reader/GermanPolarityClues-2012/GermanPolarityClues-Positive.tsv", "r", encoding="utf-8") as tsvfile:
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reader = csv.reader(tsvfile, delimiter='\t')
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for row in reader:
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if "-" not in row[4].split("/"):
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positives[row[0]] = [float(row[4].split("/")[0]), float(row[4].split("/")[1]), float(row[4].split("/")[2])]
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# get stopwords
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stopwords = []
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with open("./reader/stopwords.txt", 'r', encoding='utf-8') as f:
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for line in f:
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stopwords.append(line)
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extraSW = [".", ",", "´´", "``", "'", '"', ]
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stopwords += extraSW
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obj = Spiegel()
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NewsText = obj.read_article("https://www.spiegel.de/netzwelt/games/labo-vr-set-von-nintendo-im-test-erst-basteln-dann-staunen-a-1265633.html")
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newText = ""
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for text in NewsText:
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newText += text
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tokens = nltk.word_tokenize(newText)
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toDelete = []
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for token in tokens:
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if token in stopwords:
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toDelete.append(token)
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for token in toDelete:
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while token in tokens:
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tokens.remove(token)
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p = 0
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ne = 0
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nu = 0
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for token in tokens:
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if token in negatives:
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p += negatives[token][0]
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ne += negatives[token][1]
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nu += negatives[token][2]
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elif token in positives:
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p += positives[token][0]
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ne += positives[token][1]
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nu += positives[token][2]
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elif token in neutrals:
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p += neutrals[token][0]
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ne += neutrals[token][1]
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nu += neutrals[token][2]
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total = p + ne + nu
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p /= total
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nu /= total
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ne /= total
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print(p, nu, ne)
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