Borgmann, H., Woelm, J.-H., Merseburger, A., Nestler, T., Salem, J., Brandt, M. P., … Loeb, S. (2016). Qualitative Twitter analysis of participants, tweet strategies, and tweet content at a major urologic conference. Canadian Urological Association Journal = Journal de l’Association Des Urologues Du Canada, 10(1–2), 39–44. Retrieved December 28, 2019, from https://cuaj.ca/index.php/journal/article/view/3322/2524 .

Çalı, S., & Balaman, Ş. Y. (2019). Improved decisions for marketing, supply and purchasing: Mining big data through an integration of sentiment analysis and intuitionistic fuzzy multi criteria assessment. Computers & Industrial Engineering, 129, 315–332. https://doi.org/10.1016/J.CIE.2019.01.051 .

Cambria, E., Schuller, B., Xia, Y., & Havasi, C. (2013). New avenues in opinion mining and sentiment analysis. IEEE Intelligent Systems, 28(2), 15–21. https://doi. org/10.1109/MIS.2013.30 .

Desai, T., Shariff, A., Shariff, A., Kats, M., Fang, X., Christiano, C., & Ferris, M. (2012). Tweeting the meeting: An in-depth analysis of Twitter activity at Kidney Week 2011. PLoS One, 7(7), e40253, 1–9. https://doi.org/10.1371/journal.pone.0040253 .

Kauffmann, E., Peral, J., Gil, D., Ferrández, A., Sellers, R., & Mora, H. (2019). A framework for big data analytics in commercial social networks: A case study on sentiment analysis and fake review detection for marketing decision-making. Industrial Marketing Management, article in press. https://doi.org/10.1016/J. INDMARMAN.2019.08.003 .

Kimmons, R., & Veletsianos, G. (2016). Education scholars’ evolving uses of twitter as a conference backchannel and social commentary platform. British Journal of Educational Technology, 47(3), 445–464. https://doi.org/10.1111/bjet.12428 .

Lee, J.-S., & Back, K.-J. (2008). Attendee-based brand equity. Tourism Management, 29(2), 331–344. https://doi.org/10.1016/J.TOURMAN.2007.03.002 .

Mahrt, M., Weller, K., & Peters, I. (2014). Twitter in scholarly communication. In K. Weller, A. Burns, J. Burgess, M. Mahrt, & C. Puschmann (Eds.), Twitter and Society, Digital formations, vol. 89 (pp. 399–410). New York: Peter Lang Publishing.

Mishori, R., Levy, B., & Donvan, B. (2014). Twitter use at a family medicine conference: analyzing #STFM13. Family Medicine, 46(8), 608–614. Retrieved December 28, 2019, from http://www.ncbi.nlm.nih.gov/pubmed/25163039 .

Moore, M. T. (2017). Constructing a sentiment analysis model for LibQUAL+ comments. Performance Measurement and Metrics, 18(1), 78–87. https://doi. org/10.1108/PMM-07-2016-0031 .

Papachristopoulos, L., Ampatzoglou, P., Seferli, I., Zafeiropoulou, A., & Petasis, G. (2019). Introducing sentiment analysis for the evaluation of library’s services effectiveness. Qualitative and Quantitative Methods in Libraries, 8(1), 99–110. Retrieved December 28, 2019, from http://78.46.229.148/ojs/index.php/qqml/article/ view/515 .

Poria, S., Gelbukh, A., Cambria, E., Yang, P., Hussain, A., & Durrani, T. (2012). Merging SenticNet and WordNet-Affect emotion lists for sentiment analysis. In 2012 IEEE 11th International Conference on Signal Processing (Vol. 2, pp. 1251–1255). https:// doi.org/ 10.1109/ICoSP.2012.6491803 .

Reinhardt, W., Ebner, M., Beham, G., & Costa, C. (2009). How people are using Twitter during conferences. In V. Hornung-Prähauser & M. Luckmann (Eds.), Creativity and Innovation Competencies on the Web. Proceedings of the 5th EduMedia (pp. 145–156). Salzburg: Salzburg Research. Retrieved December 28, 2019, from http:// citeseerx.ist.psu.edu/viewdoc/download?doi=10 .1.1.148.1238&rep=rep1&type=pdf.

Ross, C., Terras, M., Warwick, C., & Welsh, A. (2011). Enabled backchannel: conference Twitter use by digital humanists. Journal of Documentation, 67(2), 214–237. https://doi.org/10.1108/00220411111109449 .

Seidel, M.-D. L. (2018). The role of conferences in the emergence of developmental professional culture. Journal of Management Inquiry, 27(2), 149–153. https://doi. org/10.1177/1056492617726271 .

Serrano-Guerrero, J., Olivas, J. A., Romero, F. P., & Herrera-Viedma, E. (2015). Sentiment analysis: A review and comparative analysis of web services. Information Sciences, 311, 18–38. https://doi.org/10.1016/J.INS.2015.03.040 .

Wood, L.C., Reiners, T., & Srivastava, H. S. (2015, September 25). Exploring sentiment analysis to improve supply chain decisions. SSRN. https://doi.org/10.2139/ssrn.2665482 .

Wu, D. D., Zheng, L., & Olson, D. L. (2014). A decision support approach for online stock forum sentiment analysis. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 44(8), 1077–1087. https://doi.org/10.1109/TSMC.2013.2295353 .