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Sentiment analysis as a tool for assessing the negative impact of tourism on a destination

Aleksandr Vetitnev, Dmitriy Chigarev, Vladlena Enushevskaya, E.S. Germanovich
2021 E3S Web of Conferences  
The authors underline predominance of positive reviews and confirms broader possibilities of the sentiment analysis method in comparison with traditional methods of studying public opinion and the possibility  ...  The visitors' reviews of the resort on TripAdvisor were studied using sentiment analysis.  ...  evaluation of the attitude of the locals and guests of host destinations towards mega-events [7, 16] .  ... 
doi:10.1051/e3sconf/202131106008 fatcat:ijbpw2ljjbb4bhjxgh2bnla7di

Perfect ratings with negative comments: Learning from contradictory patient survey responses

Andrew S Gallan, Marina Girju, Roxana Girju
2017 Patient Experience Journal  
In order to explore this phenomenon, vendor-supplied in-patient survey data from eleven different hospitals of a major U.S. health care system were utilized.  ...  A summary of comments also shows that respondents provide negative comments on issues that are outside the survey domains.  ...  Specifically, we started by looking at the distribution of comments by sentiment, as coded by the survey vendor -negative, positive, neutral and mixed comments.  ... 
doi:10.35680/2372-0247.1234 fatcat:txh2353eurdovjxb3umqayyzde

Residents' Negative Perceptions towards Tourism, Loyalty and Happiness: The Case of Fuengirola, Spain

Eva María Sánchez-Teba, María Dolores Benítez-Márquez, Teresa Romero-Navas
2019 Sustainability  
The negative perceptions of residents living in Fuengirola (Spain), divided into three dimensions (negative economic impact, negative social impact, and negative environmental impact), according to social  ...  is, an increase of loyalty was found to be associated with an increase in happiness.  ...  A Likert scale was used to evaluate the degree of agreement or disagreement with the statement on a five-point scale (1 strongly disagree, 2 disagree, 3 neutral, 4 agree, and 5 strongly agree).  ... 
doi:10.3390/su11236841 fatcat:3hvltualobflnppdflxwplb4zy

Neutrality May Matter: Sentiment Analysis in Reviews of Airbnb, Booking, and Couchsurfing in Brazil and USA [article]

Gustavo Santos, Vinicius F. S. Mota, Fabricio Benevenuto, Thiago H. Silva
2020 arXiv   pre-print
In hosting services of the sharing economy, it is common to have a personal contact between the host and guest, and this may affect users' decision to do negative reviews, as negative reviews can damage  ...  , or share access to goods and services.  ...  The authors would also like to thank Marcelo Santos and all the volunteers for the valuable help in this study.  ... 
arXiv:2005.06591v1 fatcat:godzlwd3bfgi5g2jcigiwk6qdi

Analysis on Customer Satisfaction Dimensions in P2P Accommodation using LDA: A Case Study of Airbnb

Kevin Situmorang, Achmad Hidayanto, Alfan Wicaksono, Arlisa Yuliawati
2018 Proceeding of the Electrical Engineering Computer Science and Informatics  
One of the examples is in the decision-making process about whether they will use specific products or services.  ...  People often need other's review or rating about what they are going to use or consume.  ...  After obtaining the list of hidden topics using LDA from the review document collection as the opinion targets, we try to classify each topic into positive, negative, or neutral sentiment as the evaluation  ... 
doi:10.11591/eecsi.v5.1674 fatcat:xfxbmyjnfrdb5j6qlxpz43nir4

Case Study Reports On Positive And Negative Externalities

Guillermo Vega-Gorgojo, Anna Donovan, Rachel Finn, Lorenzo Bigagli, Sebnem Rusitschka, Thomas Mestl, Paolo Mazzetti, Roar Fjellheim, George Psarros, Ovidiu Drugan, Kush Wadhwa
2015 Zenodo  
Case study reports on positive and negative externalities. Deliverable D3.2 BYTE Project.  ...  Specifically, BYTE D2.1 has already indicated that the hosting of data on US soil or by US services means that the data becomes subject to US law, which introduces a vulnerability for people whose records  ...  or just as cheap as the national aggregation services or domain aggregation services would do.  ... 
doi:10.5281/zenodo.166263 fatcat:uwyotu2isvehffvbmb4cwa4caq

What Drives Airbnb Customers' Satisfaction in Amsterdam? A Sentiment Analysis

Heyam Abdullah Bin Madhi, Muna M. Alhammah
2021 International Journal of Advanced Computer Science and Applications  
On the other hand, negative online reviews tend to be mainly linked to problems with check-in services followed by aspects related to weak host interaction, location, and room quality.  ...  Findings reveal that the polarity of Airbnb guests reviews in Amsterdam is significantly impacted by property price, value, cleanliness, rate, host communication, easiness of check-in, the accuracy of  ...  In contrast, the negative sentiments are widely affected by the host being not a super-host. Fig. 6 illustrated that 88.8% of unsatisfied customers were hosted by non-super-hosts.  ... 
doi:10.14569/ijacsa.2021.0120628 fatcat:ah3htteydbaxnpqxn3clpsoz3i

Exploring Sources of Satisfaction and Dissatisfaction in Airbnb Accommodation Using Unsupervised and Supervised Topic Modeling

Kai Ding, Wei Chong Choo, Keng Yap Ng, Siew Imm Ng, Pu Song
2021 Frontiers in Psychology  
Unlike previous LDA based Airbnb studies, this study examines positive and negative Airbnb reviews separately, and results reveal the heterogeneity of satisfaction and dissatisfaction attributes in Airbnb  ...  The results of topic distribution analysis show that in different types of Airbnb properties, Airbnb users attach different importance to the same service attributes.  ...  Sentiment Analysis in Consumer Research In the business research, sentiment analysis refers to the process of identifying different emotions (positive, negative, and neutral) toward a product or service  ... 
doi:10.3389/fpsyg.2021.659481 pmid:33967922 pmcid:PMC8096999 fatcat:g7n76aw5org2zoxijjlggiwvvy

Blog, Blogger, and the Firm: Can Negative Employee Posts Lead to Positive Outcomes?

Rohit Aggarwal, Ram Gopal, Ramesh Sankaranarayanan, Param Vir Singh
2012 Information systems research  
In contrast to the popular perception, our results reveal a potential positive aspect of negative posts.  ...  In particular, we investigate the relationship between negative posts and readership of an employee blog.  ...  of the online version at positive, negative, or neutral.  ... 
doi:10.1287/isre.1110.0360 fatcat:ybzp5fcglvcafdgbgdh27fs4wu

Performance Of Sentimental Analysis By Studying And Mining Social Media Using Parsing Technique

C. Venkatesh Muthiah
2017 Zenodo  
The opinions and sentiments are extracted from the collected data and it is fairly estimated based on the degree of quality.  ...  The principle contribution of this paper is to provide an outline for those who seek to utilize social media scraping and analytics using different software tools either in their analysis or business.  ...  Sentiments are evaluated from the extracted social media content, which may either be in positive or negative perspective.  ... 
doi:10.5281/zenodo.1134257 fatcat:sdvb6tqisrcgpn34522rr7hwge

The political economy of negative emissions technologies: consequences for international policy design

Matthias Honegger, David Reiner
2017 Climate Policy  
This includes in particular robust quantification of removed carbon under international oversight and preventing social and environmental conflicts particularly on land and water use by NETs to ensure  ...  of the Paris Agreement.  ...  Some terms that have to date been used are relatively neutral (e.g. 'backstop technology') or hopeful (e.g. 'Plan B'), whereas many others are dismissive, derisive or otherwise negative (e.g.  ... 
doi:10.1080/14693062.2017.1413322 fatcat:rw2zejdjz5funneshes5qeotlu

Service-Aware Interactive Presentation of Items for Decision-Making

Noemi Mauro, Liliana Ardissono, Sara Capecchi, Rosario Galioto
2020 Applied Sciences  
feedback aimed at making the user aware of the service properties in all the stages of fruition, focusing on the data that is most relevant to her/him.  ...  INTEREST is based on the Service Journey Maps for the design and description of user experience with services.  ...  Sentiment Analysis The sentiment analysis step is aimed at identifying the positive, neutral, or negative polarity emerging from review text.  ... 
doi:10.3390/app10165599 fatcat:nsivsvpoqbb3dgw5lmjgoi2s2e


2017 Journal of Engineering Science and Technology  
a particular product or service.  ...  They increasingly become an important data source for opinion mining and sentiment analysis, thanks to shared comments and reviews about products and services.  ...  analysis and allow the use of social OLAP.  ... 
doaj:5a4932d055824815a08f542010188782 fatcat:3eqanrwd4bgezoboqs7c3s3eva


Burçin Güçlü, David Roche, Frederic Marimon
2020 International Journal for Quality Research  
This paper investigates the reviews posted by Airbnb customers in order to assess the customer satisfaction, and to understand the criteria of Airbnb customers in short-term accommodation rentals.  ...  Results indicate that Airbnb customers are satisfied with the service they use, and that their choice of short-term accommodation on Airbnb is a multi-criterion decision process.  ...  City Number of reviews in the data analysis We also look at the sentiment polarity, meaning how positive, negative and neutral sentiments are dispersed.  ... 
doi:10.24874/ijqr14.01-17 fatcat:cbkqjg3bxvhevh3a6xsxz6662e

A Generative Language Model for Few-shot Aspect-Based Sentiment Analysis [article]

Ehsan Hosseini-Asl, Wenhao Liu, Caiming Xiong
2022 arXiv   pre-print
Further evaluation on similar sentiment analysis datasets, SST-2, SST- and OOS intent detection validates the superiority and noise robustness of generative language model in few-shot settings.  ...  Sentiment analysis is an important task in natural language processing.  ...  positive, host positive, servers positive <|category|> service positive in mi burritoaspect term <|term|> dark chicken negative, microwave taste neutral aspect category <|category|> food negative aspect  ... 
arXiv:2204.05356v1 fatcat:bhh7upamnvguxoqwce6f3f6raq
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