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LICENSE (1072, 2020-12-23)
Report.pdf (3508239, 2020-12-23)
chapter_3_notebook.ipynb (1426010, 2020-12-23)
clean.py (2097, 2020-12-23)
spam.txt (501, 2020-12-23)
stop_words.txt (2882, 2020-12-23)
utils.py (11302, 2020-12-23)

# Sentiment-analysis-of-riyadh-season-events ## NLP (Arabic Sentiment Analysis) Social media generates a huge amount of data reflecting people opinions and feelings about several events. One of the most popular social media platforms used in KSA is twitter. In this project, we will focus on analyzing Arabic tweets to identify people opinions and feelings about the cultural and entertainment events in KSA. The aim of our project is to propose a domain-specific approach for understanding sentiments expressed in tweets related to cultural and entertainment events in KSA. To achieve our goal, we have collected a sentiment dataset consists of a set of tweets related to several events. We have labelled the tweets in the dataset manually. Our final goal is to exploit machine learning to develop a sentiment analysis approach for the evaluation of the cultural and entertainment events in KSA. This approach can help the organizers of these events in identifying any negative sides in these events to avoid it in subsequent events. ### Task - **Build a data distribution system:** Around 60,000 tweets were handed to students with a detailed testing system for testing the accuracy of labeling. - **Modeling and feature extraction:** A verity of classification techniques will be applied for the best classification system ### Team members: - **Bader Abanmi**, - **Yasir Almutairi** - **Abdullah Alnomany** **Supervised by Dr. Eslam Al Maghayreh**

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