Abstract:

Social media environments have become popular platforms where people express their feelings and thoughts. Twitter is one of these platforms. Today, Twitter has become an important data source and has played a role in sentiment analysis studies in different fields. In this study, sentiment analysis was conducted on tweets about distance education during the covid-19 process. As the data set, the data set provided with open access over the Kaggle data sharing platform was used. 999 records randomly retrieved from this dataset were manually labeled as positive or negative. A sentiment analysis model was established on KNIME. This labeled data set was first prepared for analysis by preprocessing by using the appropriate nodes with KNIME, and then passed through the emotional analysis stages and a success calculation was made for the output. In the study, which was based on the dictionary-based approach, it was seen that the accuracy rate was 88.4%.

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