Year 2016, Volume 2, Issue 2, Pages 282 - 293 2016-10-19

HOW DO WE REACT @socialmedia? #catchthemoment

Mustafa COŞKUN [1] , Meltem ÖZTURAN [2]

436 305

The impact of social media on society has been growing fast, especially in the information era. While there are several studies in the literature that show the effect of social media on society, the least touched point is about the effect of social events on social media. Since the relation of social events and social media is not in one direction, this study aims to find the reaction behaviors of social media users for positive and negative events in society. Sentiments of approximately 5 million tweets of 5000 users filtered from 127 thousand were analyzed and the results showed that most positive and negative days of 2015 and first quarter of 2016 in Turkey were detected by this sentiment analysis with 69.05% accuracy. Also in this study, the effects of those social events on social media were examined in terms of reaction speed. As a result, 4 main social media reaction types were classified as “sudden impact-sudden fall”, “normal distribution”, “hear, ask, prove, react” and “one shot-long stay”.

Keywords: Social Media, Twitter, Sentiment Analysis, Social Psychology, Reaction 

  • Asur, S., & Huberman, B. A. (2010, August). Predicting the future with social media. In Web Intelligence and Intelligent Agent Technology (WI-IAT), 2010 IEEE/WIC/ACM International Conference on (Vol. 1, pp. 492-499). IEEE.
  • Chen, C. J., Ding, Y., & Kim, C. F. (2010). High-level politically connected firms, corruption, and analyst forecast accuracy around the world. Journal of International Business Studies, 41(9), 1505-1524.
  • Das, S., & Chen, M. (2001, July). Yahoo! for Amazon: Extracting market sentiment from stock message boards. In Proceedings of the Asia Pacific finance association annual conference (APFA) (Vol. 35, p. 43).
  • Dave, K., Lawrence, S., & Pennock, D. M. (2003, May). Mining the peanut gallery: Opinion extraction and semantic classification of product reviews. In Proceedings of the 12th international conference on World Wide Web (pp. 519-528). ACM.
  • Dogramaci, E. , Radcliffe, D., (2015), How turkey uses social media, Reuters Institute. Retrieved from:
  • Durahim, A. O., & Coşkun, M. (2015). # iamhappybecause: Gross National Happiness through Twitter analysis and big data. Technological Forecasting and Social Change, 99, 92-105.
  • Joshi, M., Das, D., Gimpel, K., & Smith, N. A. (2010, June). Movie reviews and revenues: An experiment in text regression. In Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics (pp. 293-296). Association for Computational Linguistics.
  • Liu, B. (2012). Sentiment analysis and opinion mining. Synthesis lectures on human language technologies, 5(1), 1-167.
  • Morinaga, S., Yamanishi, K., Tateishi, K., & Fukushima, T. (2002, July). Mining product reputations on the web. In Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 341-349). ACM.
  • Nasukawa, T., & Yi, J. (2003, October). Sentiment analysis: Capturing favorability using natural language processing. In Proceedings of the 2nd international conference on Knowledge capture (pp. 70-77). ACM.
  • O'Connor, B., Krieger, M., & Ahn, D. (2010, May). TweetMotif: Exploratory Search and Topic Summarization for Twitter. In ICWSM.
  • Pang, B., Lee, L., & Vaithyanathan, S. (2002, July). Thumbs up?: sentiment classification using machine learning techniques. In Proceedings of the ACL-02 conference on Empirical methods in natural language processing-Volume 10 (pp. 79-86). Association for Computational Linguistics.
  • Pang, B., & Lee, L. (2008). Opinion mining and sentiment analysis. Foundations and trends in information retrieval, 2(1-2), 1-135.
  • Polat, B., & Tokgöz, C. (2014). Twitter User Behaviors In Turkey: A Content Analysis On Turkish Twitter Users. Mediterranean Journal of Social Sciences,5(22), 244.
  • Reuters Institute (2015). Digital News Report 2015: How Turkey Uses Social Media. Retrieved June 27, 2016, from
  • SocialBakers (2014). Turkey is Facebook world country No. 4. Retrieved June 27, 2016, from
  • Thelwall, M., Buckley, K., Paltoglou, G., Cai, D., Kappas, A., 2010. Sentiment strength detection in short informal text. J. Am. Soc. Inf. Sci. Technol. 61, 2544–2558.
  • Tong, R. M. (2001, September). An operational system for detecting and tracking opinions in on-line discussion. In Working Notes of the ACM SIGIR 2001 Workshop on Operational Text Classification (Vol. 1, p. 6).
  • Tumasjan, A., Sprenger, T. O., Sandner, P. G., & Welpe, I. M. (2010). Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment. ICWSM, 10, 178-185.
  • Turney, P. D. (2002, July). Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews. In Proceedings of the 40th annual meeting on association for computational linguistics (pp. 417-424). Association for Computational Linguistics.
  • Vural, A.G., Cambazoglu, B.B., Senkul, P., Tokgoz, Z.O., 2013. A framework for sentiment analysis in Turkish: application to polarity detection of movie reviews in Turkish. Computer and Information Sciences III. Springer, London, pp. 437–445.
  • Yano, T., & Smith, N. A. (2010, May). What's Worthy of Comment? Content and Comment Volume in Political Blogs. In ICWSM.
  • Wiebe, J. (2000, July). Learning subjective adjectives from corpora. In AAAI/IAAI (pp. 735-740).
  • Wikipedia (2016a). Nüfuslarına göre Türkiye'deki şehirler. Wikipedia, Free Encyclopedia. Retrieved June 27, 2016, from
  • Wikipedia (2016b). 2015'te Türkiye. Wikipedia, Free Encyclopedia. Retrieved June 27, 2016, fromürkiye.
  • Wikipedia (2016c). 2016'da Türkiye. Wikipedia, Free Encyclopedia. Retrieved June 27, 2016, from
  • World Bank (2015). Urban population (% of total). Retrieved June 27, 2016, from
Journal Section Articles

Author: Mustafa COŞKUN

Author: Meltem ÖZTURAN


Publication Date: October 19, 2016

Bibtex @ { ybs287660, journal = {Yönetim Bilişim Sistemleri Dergisi}, issn = {}, eissn = {2630-550X}, address = {Vahap TECİM}, year = {2016}, volume = {2}, pages = {282 - 293}, doi = {}, title = {HOW DO WE REACT @socialmedia? \#catchthemoment}, key = {cite}, author = {COŞKUN, Mustafa and ÖZTURAN, Meltem} }
APA COŞKUN, M , ÖZTURAN, M . (2016). HOW DO WE REACT @socialmedia? #catchthemoment. Yönetim Bilişim Sistemleri Dergisi, 2 (2), 282-293. Retrieved from
MLA COŞKUN, M , ÖZTURAN, M . "HOW DO WE REACT @socialmedia? #catchthemoment". Yönetim Bilişim Sistemleri Dergisi 2 (2016): 282-293 <>
Chicago COŞKUN, M , ÖZTURAN, M . "HOW DO WE REACT @socialmedia? #catchthemoment". Yönetim Bilişim Sistemleri Dergisi 2 (2016): 282-293
RIS TY - JOUR T1 - HOW DO WE REACT @socialmedia? #catchthemoment AU - Mustafa COŞKUN , Meltem ÖZTURAN Y1 - 2016 PY - 2016 N1 - DO - T2 - Yönetim Bilişim Sistemleri Dergisi JF - Journal JO - JOR SP - 282 EP - 293 VL - 2 IS - 2 SN - -2630-550X M3 - UR - Y2 - 2019 ER -
EndNote %0 Yönetim Bilişim Sistemleri Dergisi HOW DO WE REACT @socialmedia? #catchthemoment %A Mustafa COŞKUN , Meltem ÖZTURAN %T HOW DO WE REACT @socialmedia? #catchthemoment %D 2016 %J Yönetim Bilişim Sistemleri Dergisi %P -2630-550X %V 2 %N 2 %R %U
ISNAD COŞKUN, Mustafa , ÖZTURAN, Meltem . "HOW DO WE REACT @socialmedia? #catchthemoment". Yönetim Bilişim Sistemleri Dergisi 2 / 2 (October 2016): 282-293.
AMA COŞKUN M , ÖZTURAN M . HOW DO WE REACT @socialmedia? #catchthemoment. Yönetim Bilişim Sistemleri Dergisi. 2016; 2(2): 282-293.
Vancouver COŞKUN M , ÖZTURAN M . HOW DO WE REACT @socialmedia? #catchthemoment. Yönetim Bilişim Sistemleri Dergisi. 2016; 2(2): 293-282.