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simpleScamSearcher.py
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518 lines (440 loc) · 19.7 KB
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import csv
import spacy
from scamEvaluation.scamEvaluation import ScamEvaluation
from scamEvaluation.collocation import Collocation
class SimpleScamSearcher:
def __init__(self):
self._scamEvaluator = ScamEvaluation()
self._nlp = spacy.load('en')
# Устанавливаем словосочетания, которые хотим искать в тексте
# если коэффициент в строке self._scamEvaluator.addCollocation(collocation, 0.5) положительный,
# то нахождение данного словосочетания увеличивате уровень скамности иначе понижает
# Positive collocations:
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("giving away btc")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("giving btc away")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("btc giving away")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("btc away giving")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("away btc giving")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("away giving btc")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("giving away bitcoin")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("giving bitcoin away")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("bitcoin giving away")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("bitcoin away giving")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("away bitcoin giving")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("away giving bitcoin")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("giving away eth")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("giving eth away")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("eth giving away")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("eth away giving")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("away eth giving")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("away giving eth")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("giving away etherium")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("giving etherium away")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("etherium giving away")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("etherium away giving")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("away etherium giving")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("away giving etherium")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("giveaway btc")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("btc giveaway")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("giveaway bitcoin")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("bitcoin giveaway")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("giveaway eth")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("eth giveaway")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("giveaway etherium")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
collocation.setMaxDistance(1)
tokens = self._nlp("etherium giveaway")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
separateLemmatizedWords = []
collocation = Collocation()
tokens = self._nlp("airdrop")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.3)
separateLemmatizedWords = []
collocation = Collocation()
tokens = self._nlp("multiply your investment")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 1.0)
separateLemmatizedWords = []
collocation = Collocation()
tokens = self._nlp("profit")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.4)
separateLemmatizedWords = []
collocation = Collocation()
tokens = self._nlp("profit up to")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.7)
separateLemmatizedWords = []
collocation = Collocation()
tokens = self._nlp("get up to")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.7)
separateLemmatizedWords = []
collocation = Collocation()
tokens = self._nlp("multiplied")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.3)
separateLemmatizedWords = []
collocation = Collocation()
tokens = self._nlp("triple")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.2)
separateLemmatizedWords = []
collocation = Collocation()
tokens = self._nlp("double")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.2)
separateLemmatizedWords = []
collocation = Collocation()
tokens = self._nlp("invest")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.3)
separateLemmatizedWords = []
collocation = Collocation()
tokens = self._nlp("reward")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.4)
separateLemmatizedWords = []
collocation = Collocation()
tokens = self._nlp("just send")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 1.0)
separateLemmatizedWords = []
collocation = Collocation()
tokens = self._nlp("send just")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 1.0)
separateLemmatizedWords = []
collocation = Collocation()
tokens = self._nlp("can earn")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.8)
separateLemmatizedWords = []
collocation = Collocation()
tokens = self._nlp("special bonus")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.8)
separateLemmatizedWords = []
collocation = Collocation()
tokens = self._nlp("free")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, 0.5)
# Negative collocations:
separateLemmatizedWords = []
collocation = Collocation()
tokens = self._nlp("scam")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, -1.0)
separateLemmatizedWords = []
collocation = Collocation()
tokens = self._nlp("dumm")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, -1.0)
separateLemmatizedWords = []
collocation = Collocation()
tokens = self._nlp("dumn")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, -1.0)
separateLemmatizedWords = []
collocation = Collocation()
tokens = self._nlp("stole")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, -1.0)
separateLemmatizedWords = []
collocation = Collocation()
tokens = self._nlp("awful")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, -1.0)
separateLemmatizedWords = []
collocation = Collocation()
tokens = self._nlp("fraud")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, -1.0)
separateLemmatizedWords = []
collocation = Collocation()
tokens = self._nlp("phishing")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, -1.0)
separateLemmatizedWords = []
collocation = Collocation()
tokens = self._nlp("not trust")
for token in tokens:
separateLemmatizedWords.append(token.lemma_)
collocation.setWords(separateLemmatizedWords)
self._scamEvaluator.addCollocation(collocation, -1.0)
def documentScamLevel(self, doc):
return self._scamEvaluator.scamLevel(doc)
def documentListScamLevels(self, docs):
res = []
for doc in docs:
res.append(self.documentScamLevel(doc))
return res
# Fields:
_scamEvaluator = None
_nlp = None