References
- Agarwal, A. , Xie, B. , Vovsha, I. , Rambow, O. , & Passonneau, R. (2011, June). Sentiment analysis of twitter data . Proceedings of the workshop on languages in social media (pp. 30–38). Association for Computational Linguistics.
- Andzulis, J. M. , Panagopoulos, N. G. , & Rapp, A. (2012). A review of social media and implications for the sales process. Journal of Personal Selling & Sales Management , 32 (3), 305–316.
- Asur, S. , & Huberman, B. A. (2010). Predicting the future with social media. Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology-Volume 01 (pp. 492–499). IEEE Computer Society.
- Bartov, E. , Faurel, L. , & Mohanram, P. S. (2018). Can Twitter help predict firm-level earnings and stock returns? The Accounting Review , 93 (3), 25–57.
- Bing, L. , Chan, K. C. C. , & Ou, C. (2014). Public sentiment analysis in Twitter data for prediction of a company’s stock price movements . 2014 IEEE 11th International Conference on E-Business Engineering (Icebe) (pp. 232–239). doi: 10.1109/icebe.2014.47.
- Boldt, L. C. , Vinayagamoorthy, V. , Winder, F. , Schnittger, M. , Ekran, M. , Mukkamala, R. R. , … Vatrapu, R. (2016, December). Forecasting Nike’s sales using Facebook data . 2016 IEEE International Conference on Big Data (Big Data) (pp. 2447–2456). IEEE.
- Bollen, J. , & Mao, H. (2011). Twitter mood as a stock market predictor. Computer , 44 (10), 91–94.
- Boone, T. , Ganeshan, R. , Jain, A. , & Sanders, N. R. (2019). Forecasting sales in the supply chain: Consumer analytics in the big data era. International Journal of Forecasting , 35 (1), 170–180.
- Cambria, E. (2016). Affective computing and sentiment analysis. IEEE Intelligent Systems , 31 (2), 102–107.
- Chong, D. , Li, L. , Wu, H. , Park, J. , Shi, H. , & Yan, G. (2018). Social media sentiment and bank loan contracting. Journal of Industrial Integration and Management , 03 (01), 1850007.
- Costa, E. , Ferreira, R. , Brito, P. , Bittencourt, I. I. , Holanda, O. , Machado, A. , & Marinho, T. (2012). A framework for building web mining applications in the world of blogs: A case study in product sentiment analysis. Expert Systems with Applications , 39 (5), 4813–4834.
- Cui, R. , Gallino, S. , Moreno, A. , & Zhang, D. J. (2018). The operational value of social media information. Production and Operations Management , 27 (10), 1749–1769.
- Dini, L. , Bittar, A. , Robin, C. , Segond, F. , & Montaner, M. (2017). SOMA: The smart social customer relationship management tool: Handling semantic variability of emotion analysis with hybrid technologies. In F. A. Pozzi, E. Fersini, E. Messina, & B. Liu (Eds.), Sentiment analysis in social networks (pp. 197–209). Morgan Kaufmann, Burlington, Massachusetts.
- Du, Q. , Fan, W. , Qiao, Z. , Wang, G. , Zhang, X. , & Zhou, M. (2015). Do Facebook activities increase sales? AMCIS , 2015 . Retrieved from http://aisel.aisnet.org/amcis2015/e-Biz/GeneralPresentations/33
- Duffett, R. G. (2015). Facebook advertising’s influence on intention-to-purchase and purchase amongst Millennials. Internet Research , 25 (4), 498–526.
- Fan, Z. P. , Che, Y. J. , & Chen, Z. Y. (2017). Product sales forecasting using online reviews and historical sales data: A method combining the Bass model and sentiment analysis. Journal of Business Research , 74 , 90–100.
- Fang, X. , & Zhan, J. (2015). Sentiment analysis using product review data. Journal of Big Data , 2 (1), 5.
- Feldman, R. (2013). Techniques and applications for sentiment analysis. Communications of the ACM , 56 (4), 82–89.
- Fu, J. , Shang, R. , Jeyaraj, A. , Sun, Y. , & Hu, F. (2019). Interaction between task characteristics and technology affordances: Task-technology fit and enterprise social media usage. Journal of Enterprise Information Management , 33 (1), 1–22. doi:10.1108/JEIM-04-2019-0105
- Geetha, M. , Singha, P. , & Sinha, S. (2017). Relationship between customer sentiment and online customer ratings for hotels-An empirical analysis. Tourism Management , 61 , 43–54.
- He, W. , Zha, S. , & Li, L. (2013). Social media competitive analysis and text mining: A case study in the pizza industry. International Journal of Information Management , 33 (3), 464–472.
- Hu, N. , Koh, N. S. , & Reddy, S. K. (2014). Ratings lead you to the product, reviews help you clinch it? The mediating role of online review sentiments on product sales. Decision support systems , 57 , 42–53.
- Joshi, M. , Das, D. , Gimpel, K. , & Smith, N. A. (2010, June). Movie reviews and revenues: An experiment in text regression . In The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics (pp. 293–296). Association for Computational Linguistics.
- Kapoor, K. K. , Tamilmani, K. , Rana, N. P. , Patil, P. , Dwivedi, Y. K. , & Nerur, S. (2018). Advances in social media research: Past, present and future. Information Systems Frontiers , 20 (3), 531–558.
- Kotler, P. J. (1994). Marketing management: Analysis, planning, implementation, and control (8th ed.). Englewood Cliffs.: Prentice Hall.
- Kumar, A. , Bezawada, R. , Rishika, R. , Janakiraman, R. , & Kannan, P. K. (2016). From social to sale: The effects of firm-generated content in social media on customer behavior. Journal of Marketing , 80 (1), 7–25.
- Lassen, N. B. , la Cour, L. , & Vatrapu, R. (2017). Predictive analytics with social media data. In L. Sloan & A. Quan-Haase (Eds.), The SAGE handbook of social media research methods (pp. 328–340). SAGE Publications, London.
- Lassen, N. B. , Madsen, R. , & Vatrapu, R. (2014, September). Predicting iphone sales from iphone tweets . 2014 IEEE 18th International Enterprise Distributed Object Computing Conference (pp. 81–90). IEEE.
- Lee, K. , Lee, B. , & Oh, W. (2015). Thumbs up, sales up? The contingent effect of Facebook likes on sales performance in social commerce. Journal of Management Information Systems , 32 (4), 109–143.
- Li, J. , & Xu, X. (2020). A study of Big Data-based employees’ public opinion system construction. Journal of Industrial Integration and Management , 5 (2), 225–233.
- Licht, M. H. (1995). Multiple regression and correlation.
- Liu, B. (2012). Sentiment analysis and opinion mining. Synthesis Lectures on Human Language Technologies , 5 (1), 1–167.
- Manning, C. , Surdeanu, M. , Bauer, J. , Finkel, J. , Bethard, S. , & McClosky, D. (2014). The Stanford CoreNLP natural language processing toolkit . Proceedings of 52nd annual meeting of the association for computational linguistics: System demonstrations (pp. 55–60).
- Mazzucchelli, A. , Chierici, R. , Ceruti, F. , Chiacchierini, C. , Godey, B. , & Pederzoli, D. (2018). Affecting brand loyalty intention: The effects of UGC and shopping searches via Facebook. Journal of Global Fashion Marketing , 9 (3), 270–286.
- Meire, M. , Ballings, M. , & Van den Poel, D. (2017). The added value of social media data in B2B customer acquisition systems: A real-life experiment. Decision Support Systems , 104 , 26–37.
- Micu, A. , Micu, A. E. , Geru, M. , & Lixandroiu, R. C. (2017). Analyzing user sentiment in social media: Implications for online marketing strategy. Psychology & Marketing , 34 (12), 1094–1100.
- Mishne, G. , & Glance, N. S. (2006, March). Predicting movie sales from blogger sentiment . AAAI spring symposium: Computational approaches to analyzing weblogs (pp. 155–158).
- Myers, R. H. , & Myers, R. H. (1990). Classical and modern regression with applications (Vol. 2) . Belmont, CA: Duxbury press.
- Nakov, P. , Ritter, A. , Rosenthal, S. , Sebastiani, F. , & Stoyanov, V. (2016). SemEval-2016 task 4: Sentiment analysis in Twitter . Proceedings of the 10th international workshop on semantic evaluation (semeval-2016) (pp. 1–18).
- Nguyen, T. H. , Shirai, K. , & Velcin, J. (2015). Sentiment analysis on social media for stock movement prediction. Expert Systems with Applications , 42 (24), 9603–9611.
- Oliverio, J. (2018). A survey of social media, big data, data mining, and analytics. Journal of Industrial Integration and Management , 03 (03), 1850003.
- Ortigosa, A. , Martín, J. M. , & Carro, R. M. (2014). Sentiment analysis in Facebook and its application to e-learning. Computers in Human Behavior , 31 , 527–541.
- Pandey, A. C. , Rajpoot, D. S. , & Saraswat, M. (2017). Twitter sentiment analysis using hybrid cuckoo search method. Information Processing & Management , 53 (4), 764–779.
- Pang, B. , & Lee, L. (2008). Opinion mining and sentiment analysis. Foundations and Trends® in Information Retrieval , 2 (1–2), 1–135.
- Pedhazur, E. J. , & Kerlinger, F. N. (1973). Multiple regression in behavioral research . New York: Holt, Rinehart and Winston.
- Poecze, F. , Ebster, C. , & Strauss, C. (2018). Social media metrics and sentiment analysis to evaluate the effectiveness of social media posts. Procedia Computer Science , 130 (C), 660–666.
- Saif, H. , He, Y. , Fernandez, M. , & Alani, H. (2016). Contextual semantics for sentiment analysis of Twitter. Information Processing & Management , 52 (1), 5–19.
- Severyn, A. , & Moschitti, A. (2015, August). Twitter sentiment analysis with deep convolutional neural networks . Proceedings of the 38th International ACM SIGIR conference on research and development in information retrieval (pp. 959–962). ACM.
- Studenmund, A. H. (2006). Using econometrics: A practical guide (5th ed.). Boston, MA: Pearson Education, Inc.
- Tian, X. , He, W. , Tang, C. , Li, L. , Xu, H. , & Selover, D. (2019). A new approach of social media analytics to predict service quality: Evidence from the airline industry. Journal of Enterprise Information Management . doi:10.1108/JEIM-03-2019-0086
- Wijnhoven, F. , & Plant, O. (2017). Sentiment analysis and Google trends data for predicting car sales . 38th International Conference on Information Systems 2017.
- Wu, L. , & Brynjolfsson, E. (2015). The future of prediction: How Google searches foreshadow housing prices and sales. In A. Goldfarb, S. M. Greenstein, & C. E. Tucker (Eds.), Economic analysis of the digital economy (pp. 89–118). Chicago: University of Chicago Press.
- Zou, H. , Chen, H. M. , & Dey, S. (2015). Exploring user engagement strategies and their impacts with social media mining: The case of public libraries. Journal of Management Analytics , 2 (4), 295–313.