Arabic news credibility on Twitter using sentiment analysis and ensemble learning

<p>Arabic news credibility on Twitter using sentiment analysis and ensemble learning.</p> <p>&nbsp;</p> <p>WHAT IS IT?</p> <p>-----------</p> <p>an Arabic news credibility model on Twitter using sentiment analysis and ensemble learning.</p> <p>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.</p> <p>&nbsp;</p> <p>Required Packages</p> <p>------------------</p> <ol> <li>Keras (<a href="https://keras.io/">https://keras.io/</a>).</li> <li>Scikit-learn (<a href="http://scikit-learn.org/)">http://scikit-learn.org/)</a></li> <li>Imnlearn (<a href="https://imbalanced-learn.org/stable/">imbalanced-learn documentation &mdash; Version 0.10.1</a>)</li> </ol> <p>&nbsp;</p> <p>&nbsp;</p> <p>To Run the model</p> <p>---------------</p> <p>One data file is required to run the model which are:</p> <p>&nbsp;</p> <ol> <li>The data that were used are the collected dataset in the file, set the path of the required data file in the code.</li> </ol> <p>&nbsp;</p> <p>The dataset</p> <p>---------------</p> <ol> <li>There are the dataset file with all features, you can choose the features that you need and apply it on the model.</li> <li>There are a description file that describe each feature in the news credibility dataset</li> <li>The file Tweet_ID contains the list of tweets id in the dataset.</li> <li>The annotated replies based on credibility is provided.</li> </ol> <p>&nbsp;</p> <p>&nbsp;</p> <p>&nbsp;</p> <p>&nbsp;</p> <p>CONTACTS</p> <p>--------</p> <ul> <li>If you want to report bugs or have general queries email to &lt;duha_atif@yahoo.com&gt;</li> </ul> <p>&nbsp;</p> <p>&nbsp;</p> <p>&nbsp;</p>