Arabic news credibility on Twitter using sentiment analysis and ensemble learning

Arabic news credibility on Twitter using sentiment analysis and ensemble learning.

WHAT IS IT?

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an Arabic news credibility model on Twitter using sentiment analysis and ensemble learning.

Here we include the Collected dataset and the source code of the proposed model written in Python language and using Keras library with Tensorflow backend.

Required Packages

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1. Keras (https://keras.io/).
2. Scikit-learn (http://scikit-learn.org/)
3. Imnlearn (imbalanced-learn documentation — Version 0.10.1)

To Run the model

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One data file is required to run the model which are:

1. The data that were used are the collected dataset in the file, set the path of the required data file in the code.

The dataset

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1. There are the dataset file with all features, you can choose the features that you need and apply it on the model.
2. There are a description file that describe each feature in the news credibility dataset
3. The file Tweet_ID contains the list of tweets id in the dataset.
4. The annotated replies based on credibility is provided.

CONTACTS

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• If you want to report bugs or have general queries email to <duha_atif@yahoo.com>