Towards Measuring Happiness in Saudi Arabia based on Tweets: A research proposal

Autor: Amal Abdullah AlMansour, Hamdah Abdullah Alotebii, Afnan Abdulmuin Alharbi
Rok vydání: 2018
Předmět:
Zdroj: 2018 1st International Conference on Computer Applications & Information Security (ICCAIS).
DOI: 10.1109/cais.2018.8442024
Popis: Social media platforms such as Twitter, Facebook and Blogs are growing enormously in terms of the number of users. Due to the rapid growth of the data produced from social media users, these platforms are becoming one of the most valuable data sources. Social media became outlets for people to express their thoughts, opinions, and emotions in a real-time manner. Therefore, Social media data have been utilized in literature for many sentiment analysis research. Although there have been many types of research on the sentimental analysis in English, the amount of Arabic-based sentiment analysis studies and tools are still limited. In this paper, we reviewed selected literature related to sentiment analysis in order to present a staged road map of Arabic tweets sentiment analysis in favor of measuring the happiness levels in Saudi Arabia cities. We reported the methodology to numerically represent the happiness of each city by determining the sentiment of 2000 geo-tagged tweets in Saudi Arabia using machine learning techniques. Expected results would not only rank the happiness levels for the cities in Saudi Arabia but certainly identify activities or circumstances that contribute to citizens' happiness. These expected results later can be used by institutions of related interest such as General Entertainment Authority to help planning new activities and attractions.
Databáze: OpenAIRE