Fake News Classifier

Description

Determine if news articles are Real of Fake.

Predicted Entities

REAL, FAKE

Live Demo
Open in Colab
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How to use


documentAssembler = DocumentAssembler()\
  .setInputCol("text")\
  .setOutputCol("document")

use = UniversalSentenceEncoder.pretrained(lang="en") \
  .setInputCols(["document"])\
  .setOutputCol("sentence_embeddings")


document_classifier = ClassifierDLModel.pretrained('classifierdl_use_fakenews', 'en') \
  .setInputCols(["document", "sentence_embeddings"]) \
  .setOutputCol("class")

nlpPipeline = Pipeline(stages=[documentAssembler, use, document_classifier])

light_pipeline = LightPipeline(nlp_pipeline.fit(spark.createDataFrame([['']]).toDF("text")))

annotations = light_pipeline.fullAnnotate('Donald Trump a KGB Spy? 11/02/2016 In today’s video, Christopher Greene of AMTV reports Hillary Clinton')

Results

+--------------------------------------------------------------------------------------------------------+------------+
|document                                                                                                |class       |
+--------------------------------------------------------------------------------------------------------+------------+
|Donald Trump a KGB Spy? 11/02/2016 In today’s video, Christopher Greene of AMTV reports Hillary Clinton | FAKE       |
+--------------------------------------------------------------------------------------------------------+------------+

Model Information

Model Name classifierdl_use_fakenews
Model Class ClassifierDLModel
Spark Compatibility 2.5.3
Spark NLP Compatibility 2.4
License open source
Edition public
Input Labels [document, sentence_embeddings]
Output Labels [class]
Language en
Upstream Dependencies with tfhub_use

Data Source

This model is trained on the fake new classification challenge. https://raw.githubusercontent.com/joolsa/fake_real_news_dataset/master/fake_or_real_news.csv.zip