The identification of actual and potential customers opinions and sentiments before and after purchase shapes the services offered by airlines in the airline sector as well as in every sector. In this paper, a sentiment analysis is made by compiling Twitter users' comments related to air transport. Comments of users collected from API (Application Programming Interfaces) service provided by Twitter as with many social media applications and were taken from a Java based program on a regular basis between April-May 2016. Obtained 8672 user comments were decomposed as positive, notr and negative tags. Tags are collected in a tag cloud and results are analysed with Machine Learning Method and standardized and normalized Kernel Polinoms in SMO algorithm.
With digital media becoming an important position in mass communication, information is shared and spread to those who use this media. Twitter in digital media is one of the most popular social media platforms that has come up with the combination of social network sites and blogs, with millions of members and the ability to share and spread information quickly. Sharing of information via electronic word of mouth (e-WOM) is one of the important issues that attract the attention of marketers. In this respect, this behavior of social media users is very important in sharing information by sharing, retweeting or liking of any posts on Twitter, as it is displayed by other users on their friends list. This study aims to find out the location of each destination according to the share, retweet, likes and reasons for reccommendation of users by looking at the destinations that are shared by Turkish Airlines (THY) on Twitter in 2016. The study will reveal how our country is in relation to other destinations and the tendency of Turks to other destinations to be seen in concrete terms. By using multidimensional scaling analysis, the locations of Turkey and other destinations can be displayed and evaluated in two dimensional space.
With digital media becoming an important position in mass communication, information is shared and spread to those who use this media. Twitter in digital media is one of the most popular social media platforms that has come up with the combination of social network sites and blogs, with millions of members and the ability to share and spread information quickly. Sharing of information via electronic word of mouth (e-WOM) is one of the important issues that attract the attention of marketers. In this respect, this behavior of social media users is very important in sharing information by favorite or share of any posts on Twitter, as it is displayed by other users on their friends lists. This study aims to find out the location of each destination according to the share and reasons for reccommendation of users by looking at the destinations that are shared by a scheduled Airline operating in Turkey on its official Twitter account in 2016. The study will reveal how city based destinations are in relation to others and the tendency of Turks to other destinations to be seen in concrete terms. By using multidimensional scaling analysis, the locations of destinations according to favorite and share statistics can be displayed in two dimensional space.
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