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首页> 外文期刊>Journal of Big Data >Arabia Felix 2.0: a cross-linguistic Twitter analysis of happiness patterns in the United Arab Emirates
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Arabia Felix 2.0: a cross-linguistic Twitter analysis of happiness patterns in the United Arab Emirates

机译：阿拉伯费利克斯2.0：跨语言Twitter分析阿拉伯联合酋长国的幸福模式

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Abstract The global popularity of social media platforms has given rise to unprecedented amounts of data, much of which reflects the thoughts, opinions and affective states of individual users. Systematic explorations of these large datasets can yield valuable information about a variety of psychological and sociocultural variables. The global nature of these platforms makes it important to extend this type of exploration across cultures and languages as each situation is likely to present unique methodological challenges and yield findings particular to the specific sociocultural context. To date, very few studies exploring large social media datasets have focused on the Arab world. This study examined social media use in Arabic and English across the United Arab Emirates (UAE), looking specifically at indicators of subjective wellbeing (happiness) across both languages. A large social media dataset, spanning 2013 to 2017, was extracted from Twitter. More than 17 million Twitter messages (tweets), written in Arabic and English and posted by users based in the UAE, were analyzed. Numerous differences were observed between individuals posting messages (tweeting) in English compared with those posting in Arabic. These differences included significant variations in the mean number of tweets posted, and the mean size of users networks (e.g. the number of followers). Additionally, using lexicon-based sentiment analytic tools (Hedonometer and Valence Shift Word Graphs), temporal patterns of happiness (expressions of positive sentiment) were explored in both languages across all seven regions (Emirates) of the UAE. Findings indicate that 7:00 am was the happiest hour, and Friday was the happiest day for both languages (the least happy day varied by language). The happiest months differed based on language, and there were also significant variations in sentiment patterns, peaks and troughs in happiness, associated with events of sociopolitical and religio-cultural significance for the UAE.
机译：摘要社交媒体平台的全球普及导致前所未有的数据量，其中大部分反映了个人用户的想法，观点和情感状态。对这些大型数据集的系统探索可以产生有关各种心理和社会文化变量的有价值的信息。这些平台的全球性质使得将这种类型的探索扩展到文化和语言之间变得很重要，因为每种情况都可能带来独特的方法挑战，并产生针对特定社会文化背景的发现。迄今为止，探索大型社交媒体数据集的研究很少集中在阿拉伯世界。这项研究检查了阿拉伯联合酋长国（UAE）阿拉伯语和英语的社交媒体使用情况，专门研究了两种语言的主观幸福感（幸福感）指标。从Twitter提取了2013年至2017年的大型社交媒体数据集。分析了阿拉伯联合酋长国用户用阿拉伯语和英语撰写的超过1,700万条Twitter消息（推文）。与用阿拉伯语张贴的人相比，用英语张贴信息（发推）的个人之间观察到许多差异。这些差异包括发布的平均推文数量和用户网络的平均规模（例如关注者数量）的显着差异。此外，使用基于词典的情感分析工具（Hedonometer和Valence Shift Word Graphs），在阿拉伯联合酋长国的所有七个地区（酋长国）以两种语言探索幸福的时间模式（积极情感的表达）。结果表明，两种语言的最快乐的时间是7:00，而星期五是两种语言中最快乐的一天（最不开心的一天因语言而异）。最快乐的月份因语言而异，并且在情感模式，幸福感的高峰和低谷方面也存在显着差异，这与阿联酋具有社会政治意义和宗教文化意义的事件有关。

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