Senti̇ment analysis and social media application

The change that took place in computer technology brought innovations with every step of life. The most important of these is the compilation of data in different types, the possibility of processing them, and the introduction of social media as an alternative to traditional media tools. In the past, when a given data is processed, it can be processed very easily in the unstructured data of today, while the data is pre-configured. Text mining is exactly here. Unstructured texts can now be easily processed. Emotional analysis has been a rapidly growing field of research in recent years. The main purpose of emotion analysis is to be able to reveal the sensation in the text. Social media is a concept that especially brings Web 2.0 technology and changes people's lives completely. With social media, individuals are no longer passive users who consume content that is presented to them, but become active individuals who can produce and share content themselves. Today, everyone who owns a smartphone is also a content producer. R software is one of the most frequently used open source programs in the world in recent years and can easily handle many operations. However, in our country, the value has not been perceived very well and the level of use has not reached the desired level. In this thesis, emotion analysis was done with R software. Essential texts for emotion analysis were obtained from Twitter, an important social sharing site. For sentiment analysis on Twitter, June 24, 2018 also receive the highest number of votes related to the presidential and 27. Period Vekille Nations General elections in Turkey were taken from discarded tweets related to the expected candidates and parties. Sentiment analysis was performed by tweets, the emotion score was calculated for this purpose and calculations were made by machine learning. We compared the selection results with the obtained data.