Title :
Investigating Sentimental Relation between Social Media Presence and Academic Success of Turkish Universities
Author :
Gunduz, Sedef ; Demirhan, Fatih ; Sagiroglu, Seref
Author_Institution :
Dept. of Comput. Eng., Gazi Univ., Ankara, Turkey
Abstract :
In this study an approach that uses social networking data for developing sentiment analysis system is proposed. With the help of developed software, it is tried to find out whether there is any relation between universities´ academic success and sentiment of the public about them in social media. After collecting enough text based data from Twitter, preprocessing of data is carried out and final data is trained by means of Naïve Bayes Classifier. After testing process, experimental results have shown that developed sentiment analysis system can classify the tweets about top 10 universities according to URAP rankings in terms of their sentiment with the 72.33% success rate, and proposed methodology can be used by universities for understanding sentiment of the public about them in social media.
Keywords :
Bayes methods; educational institutions; pattern classification; social networking (online); Naive Bayes classifier; Turkish universities; Twitter; URAP rankings; academic success; sentiment analysis system; sentimental relation; social media presence; social networking data; text based data; Educational institutions; Feature extraction; Media; Motion pictures; Sentiment analysis; Twitter; Academic Success; Sentiment Analysis; Social Networks; Turkish Universities; Twitter; URAP Rankings;
Conference_Titel :
Machine Learning and Applications (ICMLA), 2014 13th International Conference on
Conference_Location :
Detroit, MI
DOI :
10.1109/ICMLA.2014.95