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2019 | t. 20, z. 12, cz. 1 Agile Commerce - adaptacja technologii wobec zmienności świata | 125--139
Tytuł artykułu

Analiza sentymentu jako narzędzie monitorowania wyników finansowych przedsiębiorstwa

Treść / Zawartość
Warianty tytułu
Sentiment Analysis as a Tool for Monitoring the Company's Financial Results
Języki publikacji
PL
Abstrakty
EN
Social media is a global platform for sharing interesting ideas or news, comments and reviews. They provide a rich source of data for opinions mining in order to acquire previously unknown and useful business knowledge, which will enable not only agile management for effective customer service, but also should be reflected in the financial results of the company. The main goal of this article is to investigate whether the opinions about the company crawled from Facebook, subjected to a sentiment analysis are correlated with the enterprise's financial results. In the empirical part, Adidas company was selected for the study, and Facebook posts of its users' were collected in the period from October 1, 2014, to September 30, 2017. Existing correlations between the sentiment of users' opinions about Adidas and the financial indicators of this entity clearly show that social media play the role of tools that, if properly used through social listening, will bring financial benefits to the company.(original abstract)
Twórcy
  • Politechnika Gdańska
Bibliografia
  • Aich S., Choi K.W., Kim H.C. (2017), An approach to investigate the impact of political change on the economy of South Korea using twitter sentiment analysis, "Advanced Science Letters", ss. 10172-10176.
  • Antonio N., de Almeida A., Nunes L., Batista F., Ribeiro R. (2018), Hotel online reviews: different languages, different opinions, "Information Technology & Tourism", 18 (1-4), ss. 157-185. doi: 10.1007/s40558-018-0107-x.
  • Bagić Babac M., Podobnik V. (2018), What social media activities reveal about election results? The use of Facebook during the 2015 general election campaign in Croatia, "Information Technology and People", ss. 327-347.
  • Baj-Rogowska A. (2017), Sentiment Analysis of Facebook Posts: the Uber case, The proceedings of 2017 IEEE Eighth International Conference on Intelligent Computing and Information Systems (ICICIS'17), ISSN: 1687-1103, Cairo, Egypt, ss. 391-395.
  • Bollen J., Huina M. (2011), Twitter mood as a stock market predictor, "Computer", vol. 44, ss. 91-94.
  • Ekman P. (1993), Facial Expression and Emotion, "American Psychologist", vol. 48, ss. 384-392.
  • Gilbert E., Karahalios K. (2010), Widespread Worry and the Stock Market, Proceedings of the International Conference on Weblogs and Social.
  • Guilford J.P. (1965), Fundamental Statistics in Psychology and Education, New York.
  • Liu Y., Huang X., An A., Yu X. (2007), ARSA: a sentiment-aware model for predicting sales performance using blogs, ACM, New York, NY, USA, ss. 607-614.
  • Medhat W., Hassan A., Korashy H. (2014), Sentiment analysis algorithms and applications: A survey, "Ain Shams Engineering Journal", 5, ss. 1093-1113.
  • Öztürk N., Ayvaz S. (2017), Sentiment Analysis on Twitter: A Text Mining Approach to the Syrian Refugee Crisis, "Telematics and Informatics", doi: https://doi.org/10.1016/j.tele.2017.10.006, ss. 136-147.
  • Provalis Research (2019), ProSuite, https://provalisresearch.com/products/qualitative-dataanalysis- software/, dostęp: 12.01.2019.
  • Raport State of Social (2018), https://drive.google.com/file/d/1Kc3uwCSNWAq3d3m UTASL5z4YPQSjsX4p/view, dostęp: 4.02.2019.
  • Ruan Y., Durresi A., Alfantoukh L. (2018), Using Twitter trust network for stock market analysis, "Knowledge-Based Systems", 145, ss. 207-218. doi:10.1016/j.knosys.2018.01.016.
  • Tetlock P.C., Saar-Tsechansky M., Macskassy S. (2008), More than words: Quantifying language to measure firms' fundamentals, "The Journal of Finance", 63, ss. 1437-1467.
  • Zou L., Lam N.S.N., Cai H., Qiang Y. (2018), Mining Twitter Data for Improved Understanding of Disaster Resilience, "Annals of the American Association of Geographers", 108 (5), ss. 1422- 1441. doi:10.1080/24694452.2017.1421897.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171571217

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