The Rohingya Movement and Crisis caused a huge uproar in the political and economic state of Bangladesh. Refugee movement is a recurring event and a large amount of data in the form of opinions remains on social media such as Facebook, with very little analysis done on them.To analyse the comments based on all Rohingya related posts, we had to create and modify a classifier based on the Support Vector Machine algorithm. The code is implemented in python and uses scikit-learn library. A dataset on Rohingya analysis is not currently available so we had to use our own data set of 2500 positive and 2500 negative comments. We specifically used a support vector machine with linear kernel. A previous experiment was performed by us on the same dataset using the naive bayes algorithm, but that did not yield impressive results.
翻译:罗辛亚运动和危机在孟加拉国的政治和经济状况中引起了巨大的骚动。难民运动是一个经常性事件,在脸书等社交媒体上仍然有大量以意见形式提供的数据,对这些数据的分析很少。为了分析基于罗辛亚所有相关文章的评论,我们必须根据支持矢量机算法创建和修改一个分类器。代码在python中实施,并使用 scikit-learn 图书馆。关于罗辛亚分析的数据集目前没有提供,因此我们不得不使用我们自己的2500个正数和2500个负数数据集。我们专门使用一个带有线性内核的支持矢量机。我们以前利用天真的计算法对同一数据集进行了实验,但结果却不显著。