Scientific research

Twitter produces a massive amount of data due to its popularity that is one of the reasons underlying big data problems. One of those problems is the classification of tweets due to use of sophisticated and complex language, which makes the current tools[4] insufficient Sentiment analysis is the process of using computers to identify and categorize different points of view that are expressed in a text. The main goal of this process is to ascertain the writer’s stance that is whether positive, negative, or neutral about a given subject [7] . classifying tweets into three categories positive, negative, and neutral.the Hadoop cluster with four nodes integrated with RHadoop, Flume [3] . Twitter is a microblogging platform that generates large volumes of data with high velocity. This daily generation of unbounded and continuous data leads to Big Data streams that often require real-time distributed and fully automated processing. Twitter is an online social networking site which contains rich amount of data that can be a structured, semi-structured and un-structured data. [1]. This paper includes a collection of studies that address the same problem, and we compare certain characteristics in each study with the others. The necessary details about each study have been mentioned, including the objective, the problem we aimed to solve, the techniques, tools, and algorithms used, as well as the best-performing algorithm. هذا عبارة عن بحث علمى يجمع بين اكثر من 10 ابحاث علمية حول موضوع تحليل هاشتاجات توتير لمعرفة شعور الانسان ورأيه