Article
Version 1
This version is not peer-reviewed
Arabic X(formerly Twitter) Sentiment Analysis using Skip grams method
Version 1
: Received: 24 July 2024 / Approved: 25 July 2024 / Online: 26 July 2024 (09:09:58 CEST)
How to cite: AlEidan, R. M. Arabic X(formerly Twitter) Sentiment Analysis using Skip grams method. Preprints 2024, 2024072098. https://doi.org/10.20944/preprints202407.2098.v1 AlEidan, R. M. Arabic X(formerly Twitter) Sentiment Analysis using Skip grams method. Preprints 2024, 2024072098. https://doi.org/10.20944/preprints202407.2098.v1
Abstract
Nowadays and in the web era, there is a huge amount of information available due to automatically and easily generated websites. This information has many shared opinions from people toward different entities. Over the last decade there was a significant huge interest to determine the sentiment of any type of text especially on twitter. Twitter provides unstructured text that has many misspelling words, slang words and shortened forms. More complexity and challenges have come to the sentiment analysis researchers in the context of twitter. In this paper we conducted a literature review of the recent research of Twitter sentiment analysis on different languages. After that, we investigated challenges related to twitter sentiment analysis of Arabic language. Then we found a new solution for Sentiment analysis of Arabic twitter. So, we designed the main component of the proposed system and presented its algorithm. Finally, we performed many experiments under two kinds of datasets. The system achieves highest accuracy and shows many important results..
Keywords
Sentiment; Arabic; machine learning; Text analysis; Tweet; Social Network
Subject
Computer Science and Mathematics, Computer Science
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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