TOP 10 TURKISH UNIVERSITIES TWITTER ANALYSIS USER SENTIMENT ANALYSIS AND COMPARISON WITH INTERNATIONAL ONES

Yıl 2016, Cilt: 2 Sayı: 2, 129 - 139, 19.10.2016

Mohammed Alsadı Sevinç Gülseçen Elif Kartal

Öz

During the last 5 yeras, the importance of social media is increasing in an amazing way. Social media gives individuals, companies, organizations and many others the oppurtunity to create, share, or exchange any kind of informations such as ideas, opinions, news, media and many others. With the huge improvements in Internet and Mobile sectors access to such websites is availiable from people’s smart phones. Since users are able to create and share different types of content via social media websites, such websites became as bank of data. Huge volume of useful and valuable information could be extracted from there. ,thus, they become as one of  the primary source of information for both consumers and businesses.

Keywords twitter, user sentiment, opinion mining, text mining, features .

 

Kaynakça

• Bing, L. (2012). Sentiment analysis: A fascinating problem. In Sentiment Analysis and Opinion Mining, pages 7–143. Morgan and Claypool Publishers.
• Tan, S., Wang, Y., & Cheng, X. (2008, July). Combining learn-based and lexicon-based techniques for sentiment detection without using labeled examples. In Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (pp. 743-744). ACM.
• Han, J., Kamber, M., & Pei, J. (2011). Data mining: concepts and techniques. Elsevier.
• Khan, A. Z., Atique, M., & Thakare, V. M. (2015). Combining lexicon-based and learning-based methods for Twitter sentiment analysis. International Journal of Electronics, Communication and Soft Computing Science & Engineering (IJECSCSE), 89.
• Zhang, H., Gan, W., & Jiang, B. (2014, September). Machine Learning and Lexicon Based Methods for Sentiment Classification: A Survey. In Web Information System and Application Conference (WISA), 2014 11th (pp. 262-265). IEEE.
• URAP laboratuarı, 2015-2016 Turkey University Ranking, available online at http://tr.urapcenter.org/2015/2015_t9.php
• https://github.com/Jefferson-Henrique/GetOldTweets-java
• R Core Team (2015). R: A language and environment for statistical computing. RFoundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
• Adrian A. Dragulescu (2014). xlsx: Read, write, format Excel 2007 and Excel 97/2000/XP/2003 files. R package version 0.5.7. https://CRAN.R-project.org/package=xlsx
• Jeff Gentry (2015). twitteR: R Based Twitter Client. R package version 1.1.9 .https://CRAN.R-project.org/package=twitteR
• Timothy P. Jurka (2012). sentiment: Tools for Sentiment Analysis. R package version 0.2. https://CRAN.R-project.org/package=sentiment
• Hadley Wickham (2011). The Split-Apply-Combine Strategy for Data Analysis. Journal of Statistical Software, 40(1), 1-29. URL http://www.jstatsoft.org/v40/i01/.
• H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York,2009.
• Ian Fellows (2014). wordcloud: Word Clouds. R package version 2.5.https://CRAN.R-project.org/package=wordcloud.
• Duncan Temple Lang (2014). RJSONIO: Serialize R objects to JSON, JavaScript Object Notation. R package version 1.3-0. https://CRAN.R-project.org/package=RJSONIO