Citizen Engagement and Public Services in the Arab World: The Potential of Social Media

Mourtada, Racha; Salem, Fadi

doi:10.2139/ssrn.2578993

Cited by 34 publications

(27 citation statements)

References 5 publications

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“…The number of Arabic users on microblogging platforms such as Twitter has been rapidly increasing (Mourtada and Salem, 2014). In March 2014, the total number of active Arabic Twitter users reached 5,797,500 and the estimated number of tweets created was 533,165,900 tweets, with an average of 17,198,900 tweets per day (Mourtada and Salem, 2014).…”

Section: Introductionmentioning

confidence: 99%

“…In March 2014, the total number of active Arabic Twitter users reached 5,797,500 and the estimated number of tweets created was 533,165,900 tweets, with an average of 17,198,900 tweets per day (Mourtada and Salem, 2014). With the rapid growth of social media utilisation in the Arabic world, there also came a growth of Arabic reviews, comments, ratings, feedback and opinions.…”

Section: Introductionmentioning

confidence: 99%

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Sentiment Analysis of Arabic Tweets in e-Learning

AL-Rubaiee

Qiu

Alomar

et al. 2016

Journal of Computer Science

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Abstract:In this study, we present the design and implementation of Arabic text classification in regard to university students' opinions through different algorithms such as Support Vector Machine (SVM) and Naive Bayes (NB). The aim of the study is to develop a framework to analyse Twitter "tweets" as having negative, positive or neutral sentiments in education or, in other words, to illustrate the relationship between the sentiments conveyed in Arabic tweets and the students' learning experiences at universities. Two experiments were carried out, one using negative and positive classes only and the other one with a neutral class. The results show that in Arabic, a sentiments SVM with an n-gram feature achieved higher accuracy than NB both with using negative and positive classes only and with the neutral class.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Sentiment Analysis of Arabic Tweets in e-Learning

AL-Rubaiee

Qiu

Alomar

et al. 2016

Journal of Computer Science

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“…In the UAE, during the period of January to May 2014, 48% of these new Facebook users were within the age group of 15-29 years [19]. Furthermore, the UAE is the second highest in the Arab world to have a high penetration rate of 58%, indicating persistent growth and pervasive usage of Facebook within the UAE society [20,21].…”

Section: Public Health Communication Tools and Recommendationsmentioning

confidence: 99%

How the UAE can reduce the prevalence of obesity among the youth?- a health policy perspective

Moonesar¹,

Hickman²

2017

AOWMC

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“…Saudi Arabia is among the countries with the highest number of Twitter users among its online population (Clement, 2020;Puri-Mirza, 2019). Moreover, Saudi Arabia produces 40% of all tweets in the Arab world (Mourtada and Salem, 2014).…”

Section: Introductionmentioning

confidence: 99%

Coronavirus: Public Arabic Twitter Dataset

Addawood¹

2020

Preprint

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The COVID-19 pandemic spread of the coronavirus across the globe has affected our lives on many different levels. The world we knew before the spread of the virus has become another one. Every country has taken preventive measures, including social distancing, travel restrictions, and curfew, to control the spread of the disease. With these measures implemented, people have shifted to social media platforms in the online sphere, such as Twitter, to maintain connections. In this paper, we describe a coronavirus data set of Arabic tweets collected from January 1, 2020, primarily from hashtags populated from Saudi Arabia. This data set is available to the research community to glean a better understanding of the societal, economical, and political effects of the outbreak and to help policy makers make better decisions for fighting this epidemic.

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Citizen Engagement and Public Services in the Arab World: The Potential of Social Media

Cited by 34 publications

References 5 publications

Sentiment Analysis of Arabic Tweets in e-Learning

Sentiment Analysis of Arabic Tweets in e-Learning

How the UAE can reduce the prevalence of obesity among the youth?- a health policy perspective

Coronavirus: Public Arabic Twitter Dataset

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