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首页> 外文期刊>Journal of computer sciences >A Twitter Sentiment Analysis Model for Measuring Security and Educational Challenges: A Case Study in Saudi Arabia
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A Twitter Sentiment Analysis Model for Measuring Security and Educational Challenges: A Case Study in Saudi Arabia

机译：用于衡量安全和教育挑战的Twitter情感分析模型：以沙特阿拉伯为例

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Ensuring the good psychological health of the community is one of the highest priorities in modern societies. Therefore, having a sense of the community's rhythm and mood is a very important factor in understanding what challenges it may be facing. Psychological challenges differ from one society to another. Hence every community has its own specific psychological scales. In the context of present-day Saudi Arabia and many other countries, the measuring of educational and security challenges is critical as it can enable decision-makers to avoid anticipated risks. Traditional psychological scales in the form of questionnaires are time consuming to administer and analyze, especially where data need to be collected from a massive sample distributed over a wide geographical area. Such scales are impractical and ineffective in terms of providing critical results especially in today's rapidly changing environment. Therefore this research proposes an approach to identify and measure the educational and security challenges facing Saudi society through Twitter sentiment analysis. The psychological measurement standards of three key categories of education and security challenges were identified and broken down into selected keywords that best identified these challenges. Then Arabic tweets that contained those keywords were analyzed in order to develop a model that could classify new tweets into one of the three types of challenges. The proposed model was better able to predict tweets belonging to the cross-cultural and ethics of dialogue and rules of difference challenges than those for the dominant negative social values challenge. The results of this research show that the sentiment analysis of tweets could provide a faster and cheaper alternative to the use of traditional psychological scales.
机译：确保社区的良好心理健康是现代社会的最高优先事项之一。因此，了解社区的节奏和情绪是了解社区可能面临的挑战的非常重要的因素。心理挑战因一个社会而异。因此，每个社区都有自己特定的心理量表。在当今的沙特阿拉伯和许多其他国家中，衡量教育和安全挑战至关重要，因为它可以使决策者规避预期的风险。问卷形式的传统心理量表的管理和分析非常耗时，尤其是在需要从分布在广泛地理区域的大量样本中收集数据的地方。在提供关键结果方面，尤其是在当今瞬息万变的环境中，这样的量表是不切实际和无效的。因此，本研究提出了一种通过Twitter情绪分析来识别和衡量沙特社会面临的教育和安全挑战的方法。确定了教育和安全挑战的三个关键类别的心理测量标准，并将其分解为最能识别这些挑战的选定关键字。然后，分析包含这些关键字的阿拉伯语推文，以建立一个模型，将新推文分类为三种挑战之一。与占主导地位的负面社会价值观挑战的推文相比，该模型能够更好地预测属于跨文化和对话伦理以及差异规则挑战的推文。这项研究的结果表明，对推文的情感分析可以为使用传统心理量表提供更快，更便宜的选择。

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