Akademik Veri Yönetim Sistemi
IV. INTERNATIONAL CONGRESS ON NEW TRENDS IN SCIENCE, ENGINEERING AND TECHNOLOGY, Sankt-Peterburg, Rusya, 7 - 09 Temmuz 2020, ss.1
The increasing amount of social media usage in particularly Twitter has motivated researchers to study in this area. Because of the popularity of many of the social media platforms among all of the society in our days, these tools have been accepted as distribution channels for people’s opinions, ideas, and feelings. The increasing amount of social media usage in particularly Twitter has motivated researchers to study in this area. In this study, sentiment analysis has been performed by using classification algorithms depends on the tweets about mobile games, such as Naive Bayes, Central Based Classifier, Multi Layer Perception (MLP), and Support Vector Machines (SVM). According to experiments, we want to see which algorithm outperforms with both training and test sets. The increasing amount of social media usage in particularly Twitter has motivated researchers to study in this area. These expressions in the web have been used as important data sources for researches and analysis. The process of detection whether these data has any sentimenet and whether these sentiment positive, negative, neutral is defined as sentiment analysis. This work resulted in the perspective of mobile gaming in Turkey will be put out to be positive or negative. According to the sentiment analysis on mobile games tweets, game developers, parents and mobile game players will look at mobile games from a new perspective.