SentiSfaction: New cultural way to measure tourist COVID-19 mobility in Italy

Concetta Papapicco

doi:10.30935/mjosbr/12790

Full Text (PDF)

Concetta Papapicco ¹ ^*

More Detail

¹ University of Bari “Aldo Moro”, Bari, ITALY^* Corresponding Author

Abstract

From a psycho-linguistic and marketing perspective, the research fits into the evaluation of in the context of tourism and, in particular, tourism mobility, targeting one of the leading Italian rail transport companies, namely Trenitalia. This study, conducted on tweets, aims to examine how talks about the transport service offered by Trenitalia. A total of 674 tweets for the tourist season 2019 and 100 tweets for the tourist season 2020 were collected following the pre-COVID-19 and COVID-19 period. The methodology is the application of sentiment analysis (SA) that produces quantitative and qualitative results. For the quantitative part, the sentiment was calculated first automatically via the Sentistrength software, then an extraction of the frequencies and calculation of the dependence (Chi-square statistic and t-test) between year and polarity was conducted with R, statistical software. The results show that SA is a good methodology of analysis of the online reputation and customer satisfaction of a company that deals with tourism, also in the difference between pre-COVID-19 and COVID-19 period.

Keywords

e-tourism mobility
Twitter
sentiment analysis
customer satisfaction
COVID-19 period

License

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

MEDITERR J SOC BEH RES, Volume 7, Issue 1, February 2023, 29-41

https://doi.org/10.30935/mjosbr/12790

Publication date: 01 Jan 2023

Article Views: 1279

Article Downloads: 774

Open Access References How to cite this article

References

Alkubaisi, G. A. A. J., Kamaruddin, S. S., & Husni, H. (2018). Stock market classification model using sentiment analysis on Twitter based on hybrid naive Bayes classifiers. Computer and Information Science, 11(1), 52-64. https://doi.org/10.5539/cis.v11n1p52
Amplayo, R. K., Lee, S., & Song, M. (2018). Incorporating product description to sentiment topic models for improved aspect-based sentiment analysis. Information Sciences, 454, 200-215. https://doi.org/10.1016/j.ins.2018.04.079
Ardani, W., Rahyuda, K., Giantari, I. G. A. K., & Sukaatmadja, I. P. G. (2019). Customer satisfaction and behavioral intentions in tourism: A literature review. International Journal of Applied Business and International Management, 4(3), 84-93. https://doi.org/10.32535/ijabim.v4i3.686
Atefeh, F., & Khreich, W. (2015). A survey of techniques for event detection in twitter. Computational Intelligence, 31(1), 132-164. https://doi.org/10.1111/coin.12017
Barsky, D. (1992). Customer satisfaction in the hotel industry: Meaning and ieasurement. Hospitality Research Journal, 16(1), 51-73. https://doi.org/10.1177/109634809201600105
Basiri, M. E., Nemati, S., Abdar, M., Cambria, E., & Acharya, U. R. (2021). ABCDM: An attention-based bidirectional CNN-RNN deep model for sentiment analysis. Future Generation Computer Systems, 115, 279-294. https://doi.org/10.1016/j.future.2020.08.005
Caffi, C. (2013). Mitigation. In M. Sbisà, & K. Turner (Eds.), Pragmatics of speech actions (pp. 257). De Gruyter Mouton. https://doi.org/10.1515/9783110214383.257
Cambria, E., & Hussain, A. (2012). Sentic computing: Techniques, tools, and applications. Springer. https://doi.org/10.1007/978-94-007-5070-8
Campo, S., & Yagüe, J. M. (2009). Exploring non-linear effects of determinants on tourists’ satisfaction. International Journal of Culture, Tourism and Hospitality Research, 3(2), 127-138. https://doi.org/10.1108/17506180910962131
Campo-Martínez, S., & Garau-Vadell, J. B. (2010). The generation of tourism destination satisfaction. Tourism Economics, 16(3), 461-475. https://doi.org/10.5367/000000010792278383
Cavazza, N. (2012). Pettegolezzi e reputazione [Gossip and reputation]. Il Mulino.
Chang, J. C. (2008). Tourists’ satisfaction judgments: An investigation of emotion, equity, and attribution. Journal of Hospitality and Tourism Research, 32(1), 108-134. https://doi.org/10.1177/1096348007309571
Chatzigeorgiou, C., Christou, E., Kassianidis, P., & Sigala, M. (2009). Examining the relationship between emotions, customer satisfaction and future behavioural intentions in agrotourism. Tourismos: An International Multidisciplinary Journal of Tourism, 4(4), 145-161.
Chen, C. F., & Chen, F. S. (2010). Experience quality, perceived value, satisfaction and behavioral intentions for heritage tourists. Tourism Management, 31(1), 29-35. https://doi.org/10.1016/j.tourman.2009.02.008
Choi, T. Y., & Chu, R. (2001). Determinants of hotel guests‟ satisfaction and repeat patronage in the Hong Kong hotel industry. International Journal of Hospitality Management, 20(3), 277- 297. https://doi.org/10.1016/S0278-4319(01)00006-8
Das, S., & Chen, M. (2001). Yahoo! for Amazon: Extracting market sentiment from stock message boards. In Proceedings of the Asia Pacific Finance Association Annual Conference.
Dash, G., Kiefer, K., & Paul, J. (2021). Marketing-to-millennials: Marketing 4.0, customer satisfaction and purchase intention. Journal of Business Research, 122, 608-620. https://doi.org/10.1016/j.jbusres.2020.10.016
Dave, K., Lawrence, S., & Pennock, D. M. (2003). Mining the peanut gallery: Opinion extraction and semantic classification of product reviews. In Proceedings of WWW (pp. 519-528). https://doi.org/10.1145/775152.775226
De Kerckhove, D. (2003). La conquista del tempo. Società e democrazia nell’era della rete [The conquest of time. Society and democracy in the Internet age]. Editori Riuniti.
Deaden, P., & Harron, S. (1994). Alternative tourism and adaptive change. Annals of Tourism Research, 21(1), 81-102. https://doi.org/10.1016/0160-7383(94)90006-X
Della Corte, V., Sciarelli, M., Cascella, C., & Del Gaudio, G. (2015). Customer satisfaction in tourist destination: The case of tourism offer in the city of Naples. Journal of Investment and Management, 4(1-1), 39-50. https://doi.org/10.11648/j.jim.s.2015040101.16
Deng, W. J., Yeh, M. L., & Sung, M. L. (2013). A customer satisfaction index model for international tourist hotels: Integrating consumption emotions into the American customer satisfaction index. International Journal of Hospitality Management, 35, 133-140. https://doi.org/10.1016/j.ijhm.2013.05.010
Fah, L. K., & Kandasamy, S. (2011). An investigation of service quality and customer satisfaction among hotels in Langkawi. In Proceedings of the International Conference on Management.
Ginieis, M., Sánchez-Rebull, M-V., & Campa-Planas, F. (2012). The academic journal literature on air transport: Analysis using systematic literature review methodology. Journal of Air Transport Management, 19, 31-35. https://doi.org/10.1016/j.jairtraman.2011.12.005
Gountas, J., & Gountas, S. (2007). Personality orientations, emotional states, customer satisfaction, and intention to repurchase. Journal of Business Research, 60(1), 72-75. https://doi.org/10.1016/j.jbusres.2006.08.007
Gui, M. (2014). A dieta di media [On a medium diet]. Il Mulino.
Gummesson, E. (1998). Relationship marketing as a paradigm shift: Some conclusions from the 30R approach. Management Decision, 35(3-4), 267-272. https://doi.org/10.1108/00251749710169648
Hoyer, W. D., & MacInnis, D. J. (2001). Consumer behaviour. Houghton Mifflin Company.
Huang, H. H., Chiu, C. K., & Kuo, C. (2006). Exploring customer satisfaction, trust and destination loyalty in tourism. Journal of American Academy of Business, 10(1), 156-159. https://doi.org/10.1108/BIJ-04-2015-0038
Hult, G. T. M., Sharma, P. N., Morgeson III, F. V., & Zhang, Y. (2019). Antecedents and consequences of customer satisfaction: do they differ across online and offline purchases? Journal of Retailing, 95(1), 10-23. https://doi.org/10.1016/j.jretai.2018.10.003
Hwang, J., & Han, H. (2014). Examining strategies for maximizing and utilizing brand prestige in the luxury cruise industry. Tourism Management, 40, 244-259. https://doi.org/10.1016/j.tourman.2013.06.007
Iaquinto, B. L. (2020). Tourist as vector: Viral mobilities of COVID-19. Dialogues in Human Geography, 10(2), 174-177. https://doi.org/10.1177/2043820620934250
James, W. (1955). Pragmatism. Merridian Books.
Kaur, H., Ahsaan, S. U., Alankar, B., & Chang, V. (2021). A proposed sentiment analysis deep learning algorithm for analyzing COVID-19 tweets. Information Systems Frontiers, 13, 1417-1429. https://doi.org/10.1007/s10796-021-10135-7
Kirelli, Y., & Arslankaya, S. (2020). Sentiment analysis of shared tweets on global warming on Twitter with data mining methods: A case study on Turkish language. Computational Intelligence and Neuroscience, 2020, 1904172.https://doi.org/10.1155/2020/1904172
Koc, E. (2006). Total quality management and business excellence in services: The implications of all-inclusive pricing system on internal and external customer satisfaction in the Turkish tourism market. Total Quality Management & Business Excellence, 17(7), 857-877. https://doi.org/10.1080/14783360600595252
Konietschke, F., Placzek, M., Schaarschmidt, F., & Hothorn, L. A. (2015). nparcomp: An R software package for nonparametric multiple comparisons and simultaneous confidence intervals. Journal of Statistical Software, 64(9), 1-17. https://doi.org/10.18637/jss.v064.i09
Lee, K.-W., Kim, H.-B., Kim, H.-S., & Lee, D.-S. (2010). The determinants of factors in FIT guests’ perception of hotel location. Journal of Hospitality and Tourism Management, 17(1), 167-174. https://doi.org/10.1375/jhtm.17.1.167
Leingpibul, T., Thomas, S. Broyles, A., & Ross R. H. (2009). Loyalty’s influence on the consumer satisfaction and (re)purchase behavior relationship. Journal of Consumer Satisfaction: Dissatisfaction and Complaining Behavior, 22, 36-53.
Lindberg, K., & Johnson, R. L. (1997). The economic values of tourism’s social impacts. Annals of Tourism Research, 24(1), 90-116. https://doi.org/10.1016/S0160-7383(96)00033-3
Lindberg, K., Andersson, T. D., & Dellaert, B. G. (2001). Tourism development: Assessing social gains and losses. Annals of Tourism Research, 28(4), 1010-1030. https://doi.org/10.1016/S0160-7383(01)00007-X
Loureiro, S. M. C. (2010). Satisfying and delighting the rural tourists. Journal of Travel and Tourism Marketing, 27(4), 396-408. https://doi.org/10.1080/10548408.2010.481580
Loureiro, S. M. C., & Kastenholz, E. (2011). Corporate reputation, satisfaction, delight, and loyalty towards rural lodging units in Portugal. International Journal of Hospitality Management, 30(3), 575-583. https://doi.org/10.1016/j.ijhm.2010.10.007
Manuti, A., Cortini, M., & Mininni, G. (2007). La costruzione discorsiva della meta nelle campagne di promozione turistica [The discursive construction of the destination in tourism promotion campaigns]. Turismo e Psicologia [Tourism and Psychology], 1(1), 116-127.
Martin, D. S., & O’Neill, M. (2010). Scale development and testing: A new measure of cognitive satisfaction in sports tourism. Event Management, 14(1), 1-15. https://doi.org/10.3727/152599510X12724735767471
McIntosh, R., & Goeldner, C. (1984). Tourism: Principles, practice, philosophies. Grid Publication.
Mereu, A. (2004). La psicologia del turismo [The psychology of tourism]. HT Psico-Pratika [HT Psycho-Practice], 11, 1-3.
Mereu, A. (2010). La motivazione al turismo [Motivation for tourism]. HT Psico-Pratika [HT Psycho-Practice], 16, 1-4.
Molinari, L., Abratt, R., & Dion, P. (2008). Satisfaction, quality, and value and effects on the repurchase and positive word of mouth behavioural intentions in a business to business services context. Journal of Services Marketing, 22(5), 363-373. https://doi.org/10.1108/08876040810889139
Motlagh, A. T., Sadeh, E., Sadeh, S., Jafari, H., Morovat, J. A., & Enaamzadeh A. (2013). How does service quality lead to loyalty in the hotel industry in Iran. Research Journal of Applied Sciences, Engineering and Technology, 5(2), 347-379. https://doi.org/10.19026/rjaset.5.4961
Nowak, J., & Sahli, M. (2007). Coastal tourism and “Dutch disease” in a small island economy. Tourism Economics, 13(1), 49-65. https://doi.org/10.5367/000000007779784452
Pang, B., & Lee, L. (2008). Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval, 2(1-2), 1-135. https://doi.org/10.1561/1500000011
Papapicco, C. (2020). Google mini: Italian example of artificial prosociality. Online Journal of Communication and Media Technologies, 10(3), e202015. https://doi.org/10.29333/ojcmt/7995
Perelman, C., & Olbrechts-Tyteca, L. (1958). Trait de l’argumentation. La nouvelle rhettorique [Line of argument. The new rhetoric]. Presses Universitaires de France.
Peverini, P. (2014). Environmental issues in unconventional social advertising: A semiotic perspective. Semiotica, 199, 219-246. https://doi.org/10.1515/sem-2013-0126
Picard, R. W. (2000). Toward computers that recognize and respond to user emotion. IBM Systems Journal, 39(3-4), 705-719. https://doi.org/10.1147/sj.393.0705
Prastowo, E. Y., & Yuniarno, E. M. (2019). Combining SentiStrength and multilayer perceptron in Twitter sentiment classification. In Proceedings of the 2019 International Seminar on Intelligent Technology and Its Applications (pp. 381-386). https://doi.org/10.1109/ISITIA.2019.8937134
Prensky, M. (2001). Digital natives, digital immigrants. On the Horizon, 9(5), 1-6. https://doi.org/10.1108/10748120110424843
Pulcini, E. (2006). Click TV. Come Internet e il digitale cambieranno la television [Click TV. How the Internet and digital will change television]. Franco Angeli.
Rathnayake, M. (2015). How does ‘crowding’ affect visitor satisfaction at the Horton Plains National Perk in Sri Lanka? Tourism Management Perspectives, 16, 129-138. https://doi.org/10.1016/j.tmp.2015.07.018
Ravishankar, B., & Christopher, P. B. (2020). Impact of innovative services on customer satisfaction and enhancing tourism: airline and hotel services from a tourist perspective. Journal of Critical Reviews, 7(11), 705-711.
Riva, G., Wiederhold, B. K., & Cipresso, P. (2015). Psychology of social media: From technology to identity. In G. Riva, B. K. Wiederhold, & P. Cipresso (Eds.), The psychology of social networking: Personal experience in online communities (pp. 1-11). De Gruyter Open. https://doi.org/10.1515/9783110473780
Sánchez-Rebull, M. V., Rudchenko, V., & Martín, J. C. (2018). The antecedents and consequences of customer satisfaction in tourism: a systematic literature review. Tourism and Hospitality Management, 24(1), 151-183. https://doi.org/10.20867/thm.24.1.3
Sari, E. Y., Wierfi, A. D., & Setyanto, A. (2019). Sentiment analysis of customer satisfaction on transportation network company using naive Bayes classifier. In Proceedings of the 2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia (pp. 1-6). IEEE. https://doi.org/10.1109/CENIM48368.2019.8973262
Sharma, G. D., Thomas, A., & Paul, J. (2021). Reviving tourism industry post-COVID-19: A resilience-based framework. Tourism Management Perspectives, 37, 100786. https://doi.org/10.1016/j.tmp.2020.100786
Smith, S. L. (1998). The tourism product. Annals of Tourism Research, 21, 582-595. https://doi.org/10.1016/0160-7383(94)90121-X
Taboada, M., Brooke, J., Tofiloski, M., Voll, K., & Stede, M. (2011). Lexicon-based methods for sentiment analysis. Computational Linguistics, 37(2), 267-307. https://doi.org/10.1162/COLI_a_00049
Tasci, A. D., & Boylu, Y. (2010). Cultural comparison of tourists’ safety perception in relation to trip satisfaction. International Journal of Tourism Research, 12(2), 179-192. https://doi.org/10.1002/jtr.745
Tong, R. M. (2001). An operational system for detecting and tracking opinions in on-line discussions. In Proceedings of the Working Notes of the ACM SIGIR Workshop on Operational Text Classification (pp. 1-6).
Torre, A., & Scarborough, H. (2017). Reconsidering the estimation of the economic impact of cultural tourism. Tourism Management, 59, 621-629. https://doi.org/10.1016/j.tourman.2016.09.018
van Raaij, W. F., & Francken, D. A. (1984). Vacation decisions, activities, and satisfactions. Annals of Tourism Research, 11(1), 101-112. https://doi.org/10.1016/0160-7383(84)90098-7
Zhang, Z., Ye, Q., Song, H., & Liu, T. (2014). The structure of customer satisfaction with cruise-line services: An empirical investigation based on online word of mouth. Current Issues in Tourism, 18(5), 450-464. https://doi.org/10.1080/13683500.2013.776020
Zhou, L., Ye, S., Pearce, P. L., & Wu, M. (2014). Refreshing hotel satisfaction studies by reconfiguring customer review data. International Journal of Hospitality Management, 38, 1-10. https://doi.org/10.1016/j.ijhm.2013.12.004

How to cite this article

APA

Papapicco, C. (2023). SentiSfaction: New cultural way to measure tourist COVID-19 mobility in Italy. Mediterranean Journal of Social & Behavioral Research, 7(1), 29-41. https://doi.org/10.30935/mjosbr/12790

Vancouver

Papapicco C. SentiSfaction: New cultural way to measure tourist COVID-19 mobility in Italy. MEDITERR J SOC BEH RES. 2023;7(1):29-41. https://doi.org/10.30935/mjosbr/12790

AMA

Papapicco C. SentiSfaction: New cultural way to measure tourist COVID-19 mobility in Italy. MEDITERR J SOC BEH RES. 2023;7(1), 29-41. https://doi.org/10.30935/mjosbr/12790

Chicago

Papapicco, Concetta. "SentiSfaction: New cultural way to measure tourist COVID-19 mobility in Italy". Mediterranean Journal of Social & Behavioral Research 2023 7 no. 1 (2023): 29-41. https://doi.org/10.30935/mjosbr/12790

Harvard

Papapicco, C. (2023). SentiSfaction: New cultural way to measure tourist COVID-19 mobility in Italy. Mediterranean Journal of Social & Behavioral Research, 7(1), pp. 29-41. https://doi.org/10.30935/mjosbr/12790

MLA

Papapicco, Concetta "SentiSfaction: New cultural way to measure tourist COVID-19 mobility in Italy". Mediterranean Journal of Social & Behavioral Research, vol. 7, no. 1, 2023, pp. 29-41. https://doi.org/10.30935/mjosbr/12790