Abstract
The paper addresses the issue of the possibility of using sentiment analysis tools to support the management of local government entities. The author team carried out research in this field in several dozen municipalities in the northern part of the Silesian Voivodship. Among the analyzed issues, the information resources which are or should be collected for the purpose of managing municipalities were analyzed. The issue of municipal management was divided into three aspects: management of municipal offices, management of commune assets and resources, and community management. The paper presents sentiment analysis tools and a description of potential information resources that are or should be collected. The conclusions indicated fundamental barriers to the use of sentiment analysis tools for municipal management purpose.
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References
Asghar, M.Z., Khan, A., Ahmad, S., Quasim, M., Khan, I.A.: Lexicon-enhanced sentiment analysis framework using rule-based classification scheme. PLoS ONE 12(2), e0171649 (2017). https://doi.org/10.1371/journal.pone.0171649
Jelonek, D., Stępniak, C., Ziora, L.: The meaning of big data in the support of managerial decisions in contemporary organizations: review of selected research. In: Proceedings of 2018 Future of Information and Communication Conference, Singapore. IEEE New York, pp. 195–198 (2018)
Farhadloo, M., Rolland, E.: Fundamentals of sentiment analysis and its applications. In: Pedrycz, W., Chen, S.M. (eds.) Sentiment Analysis and Ontology Engineering. Studies in Computational Intelligence, vol. 639. Springer International Publishing, Switzerland (2016)
Liu, B.: Sentiment Analysis and Opinion Mining. Morgan & Claypool Publishers (2012). www.cs.uic.edu/~liub/FBS/SentimentAnalysis-and-OpinionMining.pdf. Accessed 10 May 2018
Ziora, L.: The Sentiment Analysis as a Tool of Business Analytics in Contemporary Organizations. Economics Studies. University of Economics in Katowice Research Papers, no 281, Katowice, pp. 234–241 (2016)
Goss, M., Głowacka, N.: Introduction to sentiment analysis (in Polish), goo.gl/p 1I3mD. Accessed 10 May 2018
Medhat, W., Hassan, A., Korashy, H.: Sentiment analysis algorithms and applications: a survey. Shams Eng. J. 5(4), 1093–1113. www.sciencedirect.com/science/article/pii/S2090447914000550. Accessed 10 May 2018
Tomanek, K.: Sentiment analysis – method of qualitative data analysis. An example of application and evaluation of RID glossary and Bayes classification method in qualitative data analysis. In: Review of Qualitative Sociology (in Polish), vol. 10, no. 2, pp. 118–136. www.przegladsocjologiijakosciowej.org. Accessed 10 May 2018
Bing Liu’s Opinion Lexicon. https://goo.gl/9rNgVy. Accessed 10 May 2018
Sentiwordnet.isti.cnr.it. Accessed 10 May 2018
http://mpqa.cs.pitt.edu. Accessed 10 May 2018
Sentiment Symposium Tutorial: Lexicons. http://sentiment.christopherpotts.net/lexicons.html. Accessed 10 May 2018
Sentiment Analysis with Python NLTK Text Classification. http://text-processing.com/demo/sentiment. Accessed 10 May 2018
www.sentiment140.com. Accessed 10 May 2018
goo.gl/qdeac. Accessed 10 May 2018
Saif, H., He, Y., Fernandez, M., Alani, H.: Semantic Patterns for Sentiment Analysis of Twitter. Springer, Heidelberg. https://link.springer.com/content/pdf/10.1007%2F978-3-319-11915-1_21.pdf
Ren, F., Wang, L.: Sentiment analysis of text based on three-way decisions. J. Intell. Fuzzy Syst. 33, 245–254 (2017)
Agarwal, A., Xie, B., Vovsha, I., Rambow, O., Passonneau, R.: Sentiment analysis of twitter data. In: Proceedings of the Workshop on Language in Social Media (LSM 2011), Portland, Oregon, pp. 30–38, 23 June 2011
www.sas.com. Accessed 10 May 2018
Dzieciątko, M.: Text Mining and Everyday Reality. www.sas.com. Accessed 10 May 2018
Feldman, R.: Techniques and applications for sentiment analysis. Commun. ACM 56(4) (2013)
Liu, Z., Ng, E.Y.K.: When siri knows how you feel: study of machine learning in automatic sentiment recognition from human speech. In: Proceedings of Future of Information and Communication Conference (FICC), Singapore, pp. 661–665 (2018)
Jelonek, D., Stępniak, C., Turek, T.: The concept of building regional business spatial community. In: 10th International Joint Conference on e-Business and Telecommunications. Proceedings, ICETE 2013, Reyklavik, Iceland, 29–31 July, SCITEPRESS—Science and Technology Publications, pp. 83–90 (2013)
Antonopoulos, Ch.G., Shang, Y.: Opinion formation in multiplex networks with general initial distributions. Nat. Sci. Rep. 8, Article Number 2852 (2018). https://www.nature.com/articles/s41598-018-21054-0
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Jelonek, D., Mesjasz-Lech, A., Stępniak, C., Turek, T., Ziora, L. (2020). Potential Data Sources for Sentiment Analysis Tools for Municipal Management Based on Empirical Research. In: Arai, K., Bhatia, R. (eds) Advances in Information and Communication. FICC 2019. Lecture Notes in Networks and Systems, vol 69. Springer, Cham. https://doi.org/10.1007/978-3-030-12388-8_49
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