scholarly journals Airbnb or Hotel?

2020 ◽  
Vol 4 (2) ◽  
pp. 1-10
Author(s):  
Zhiyong Li ◽  
Honglin Chen ◽  
Xia Huang
Keyword(s):  
Information Technology ◽  
Social Media ◽  
Big Data ◽  
Online Reviews ◽  
Tourism Industry ◽  
Sources Of Information ◽  
Value For Money ◽  
Consumer Awareness ◽  
Positive Sentiment ◽  
Negative Sentiment

Advances in information technology have hugely influenced the tourism industry. Many tourists can generate and share their travel tips through social media, and people consult online reviews before making travel arrangements because they could access these sources of information easily. Either positive or negative reviews could increase consumer awareness of Airbnb. Using the approach of text mining and sentiment analysis, examining whether guests' emotions are positive or negative, this study investigates the attributes that influence Airbnb consumers' experiences compared with their previous hotel experiences by analysing big data of guests' online reviews. Findings reveal that the factors of guests' positive sentiment are the atmosphere, flexibility, special amenities, and humanized service; the factors of guests' negative sentiment are not value for money, have to clean the room before leaving, sharing amenities and space with strangers, disturbed by hosts' noisy recreational activities, and troubled by hosts' requesting good reviews.

scholarly journals Twitter content analysis of the Australian bushfires disaster 2019-2020: futures implications

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gregory Willson ◽  
Violetta Wilk ◽  
Ruth Sibson ◽  
Ashlee Morgan
Keyword(s):  
Social Media ◽  
Design Methodology ◽  
Qualitative Data ◽  
Political Action ◽  
Tourism Industry ◽  
Media Content ◽  
Data Set ◽  
Content Type ◽  
Positive Sentiment ◽  
Negative Sentiment

Purpose This paper aims to explore the themes and nature of sentiment of Twitter content that discussed the Australian bushfire disaster 2019–2020 and its associated wildlife devastation, with considerations for the future of Australia’s tourism industry. Design/methodology/approach A large, qualitative data set consisting of all publicly available Twitter posts during the period of the Australian bushfires from December 2019 to March 2020 that mentioned the bushfires and wildlife are explored. Findings The devastation of wildlife through the Australian bushfire disaster elicited emotionally charged Twitter content from both Australian and overseas users. Positive sentiment focused on offering support to areas impacted by wildlife devastation. Negative sentiment concentrated on linking the Australian bushfires disaster to global discussions surrounding the climate emergency, and a perceived lack of political action. Originality/value Despite the intensity of media attention directed towards the Australian bushfires disaster 2019–2020, there has been little scholarly research exploring social media content specifically focused on the wildlife devastation and its association with, and implications for, the tourism industry.

scholarly journals Trends in Patient, Physician, and Public Perception of Ulnar Collateral Ligament Reconstruction Using Social Media Analytics

2021 ◽  
Vol 9 (3) ◽  
pp. 232596712199005
Author(s):  
Jonathan S. Yu ◽  
James B. Carr ◽  
Jacob Thomas ◽  
Julianna Kostas ◽  
Zhaorui Wang ◽  
...  
Keyword(s):  
Social Media ◽  
Public Perception ◽  
Ulnar Collateral Ligament ◽  
Return To Play ◽  
Social Media Analytics ◽  
Care Providers ◽  
Collateral Ligament ◽  
The Past ◽  
Positive Sentiment ◽  
Negative Sentiment

Background: Social media posts regarding ulnar collateral ligament (UCL) injuries and reconstruction surgeries have increased in recent years. Purpose: To analyze posts shared on Instagram and Twitter referencing UCL injuries and reconstruction surgeries to evaluate public perception and any trends in perception over the past 3 years. Study Design: Cross-sectional study. Methods: A search of a 3-year period (August 2016 and August 2019) of public Instagram and Twitter posts was performed. We searched for >22 hashtags and search terms, including #TommyJohn, #TommyJohnSurgery, and #tornUCL. A categorical classification system was used to assess the sentiment, media format, perspective, timing, accuracy, and general content of each post. Post popularity was measured by number of likes and comments. Results: A total of 3119 Instagram posts and 267 Twitter posts were included in the analysis. Of the 3119 Instagram posts analyzed, 34% were from patients, and 28% were from providers. Of the 267 Twitter posts analyzed, 42% were from patients, and 16% were from providers. Although the majority of social media posts were of a positive sentiment, over the past 3 years, there was a major surge in negative sentiment posts (97% increase) versus positive sentiment posts (9% increase). Patients were more likely to focus their posts on rehabilitation, return to play, and activities of daily living. Providers tended to focus their posts on education, rehabilitation, and injury prevention. Patient posts declined over the past 3 years (–28%), whereas provider posts increased substantially (110%). Of posts shared by health care providers, 4% of posts contained inaccurate or misleading information. Conclusion: The majority of patients who post about their UCL injury and reconstruction on social media have a positive sentiment when discussing their procedure. However, negative sentiment posts have increased significantly over the past 3 years. Patient content revolves around rehabilitation and return to play. Although patient posts have declined over the past 3 years, provider posts have increased substantially with an emphasis on education.

scholarly journals Analysis of Social Media Users Sentiments against Omnibus Law Based on Hashtags on Twitter

SISTEMASI ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 197
Author(s):  
Okta Fanny ◽  
Heri Suroyo
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Main Topic ◽  
Accuracy Score ◽  
Test Results ◽  
Bayes Classifier ◽  
The Public ◽  
Average Accuracy ◽  
Positive Sentiment ◽  
Negative Sentiment

From the research that has been done, it can be concluded that Sentiment Analysis can be used to know the sentiment of the public, especially Twitter netizens against omnibus law. After the sentiment analysis, it looks neutral artmen with the largest percentage of 55%, then positive sentiment by 35% and negative sentiment by 10%. The results of the analysis showed that the Naïve Bayes Classifier method provides classification test results with accuracy in Hashtag Pro with an average accuracy score of 92.1%, precision values with an average of 94.8% and recall values with an average of 90.7%. While Hashtag Counter For data classification, with an average accuracy value of 98.3%, precision value with an average of 97.6% and recall value with an average of 98.7%. The result of text cloud analysis conducted on a combination of hashtags both Hashtag pros and Hashtags cons, the dominant word appears is Omnibus Law which means that all hashtags in scrap is really discussing the main topic that is about Omnibus Law

scholarly journals Airline passengers’ perceptions of service quality: themes in online reviews

2019 ◽  
Vol 31 (2) ◽  
pp. 855-873 ◽  
Author(s):  
Ana Brochado ◽  
Paulo Rita ◽  
Cristina Oliveira ◽  
Fernando Oliveira
Keyword(s):  
Social Media ◽  
Design Methodology ◽  
Online Reviews ◽  
Value For Money ◽  
Content Type ◽  
The Core ◽  
Content Analyses ◽  
Airline Passengers ◽  
Media Platform ◽  
Post Purchase

PurposeThis paper aims to identify the main themes shared in online reviews by airline travellers, as well as which of these themes were linked with higher and lower value for money ratings.Design/methodology/approachThe research used mixed content analyses (i.e. quantitative and qualitative) to examine 1,200 reviews of six airline companies shared by airline travellers in a social media platform.FindingsThe analyses revealed nine themes in descriptions of airline travel experiences. These are the core services during “flights”, “airport” operations, crew and ground “staff”, ticket “classes”, “seats”, inflight “services”, “entertainment”, overall experiences of “airlines” and post-purchase recommendations of with which companies to “fly”. Low value for money ratings are linked with the “airport” and “flights” themes.Originality/valueThe results offer useful insights into airline travellers’ overall experiences based on social media information and facilitate the identification of the main themes linked with different value for money ratings.

eWOW of Guests Regarding Their Hotel Experience

2020 ◽  
pp. 295-308
Author(s):  
Zelia Breda ◽  
Rui Costa ◽  
Gorete Dinis ◽  
Amandine Angie Martins
Keyword(s):  
Sentiment Analysis ◽  
Online Reviews ◽  
User Generated Content ◽  
Sources Of Information ◽  
Value For Money ◽  
Quality Of Sleep ◽  
Online Comments ◽  
Analytical Response ◽  
Source Of Information

Online comments are increasingly mentioned as an important source of information, simplifying consumers' buying decisions. Online user-generated content has become one of the main sources of information for tourists, who themselves become creators of their own online content. This chapter focuses on sentiment analysis of comments made on TripAdvisor regarding one resort located in the Algarve region, in Portugal. The resort has good reviews, which means that the eWOM is positive. The highest scores relate to the resort's cleanliness, location and quality of sleep, and those that were less relevant were the value for money, the rooms and the service. The most dominant emotion is joy, followed by an analytical response. Negative emotions, such as sadness and anger, were not found very often in the online reviews. These results could be explained by the quality of the service, the kindness of the staff, the facilities for children, the entertainment, and the location, attributes that were often highlighted in the comments.

scholarly journals Mining social media data to investigate patient perceptions regarding DMARD pharmacotherapy for rheumatoid arthritis

2020 ◽  
Vol 79 (11) ◽  
pp. 1432-1437 ◽  
Author(s):  
Chanakya Sharma ◽  
Samuel Whittle ◽  
Pari Delir Haghighi ◽  
Frada Burstein ◽  
Roee Sa'adon ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Social Media ◽  
Side Effects ◽  
Sentiment Analysis ◽  
Computer Algorithms ◽  
Social Media Platforms ◽  
Synthetic Agents ◽  
Positive Sentiment ◽  
Negative Sentiment ◽  
Media Data

ObjectivesWe hypothesise that patients have a positive sentiment regarding biological/targeted synthetic disease modifying anti-rheumatic drugs (b/tsDMARDs) and a negative sentiment towards conventional synthetic agents (csDMARDs). We analysed discussions on social media platforms regarding DMARDs to understand the collective sentiment expressed towards these medications.MethodsTreato analytics were used to download all available posts on social media about DMARDs in the context of rheumatoid arthritis. Strict filters ensured that user generated content was downloaded. The sentiment (positive or negative) expressed in these posts was analysed for each DMARD using sentiment analysis. We also analysed the reason(s) for this sentiment for each DMARD, looking specifically at efficacy and side effects.ResultsComputer algorithms analysed millions of social media posts and included 54 742 posts about DMARDs. We found that both classes had an overall positive sentiment. The ratio of positive to negative posts was higher for b/tsDMARDs (1.210) than for csDMARDs (1.048). Efficacy was the most commonly mentioned reason in posts with a positive sentiment and lack of efficacy was the most commonly mentioned reason for a negative sentiment. These were followed by the presence/absence of side effects in negative or positive posts, respectively.ConclusionsPublic opinion on social media is generally positive about DMARDs. Lack of efficacy followed by side effects were the most common themes in posts with a negative sentiment. There are clear reasons why a DMARD generates a positive or negative sentiment, as the sentiment analysis technology becomes more refined, targeted studies could be done to analyse these reasons and allow clinicians to tailor DMARDs to match patient needs.

scholarly journals New Media in Public Relations: A Study of New Media in Ragunan Zoo as a Tourism Destination

2020 ◽  
Vol 1 (1) ◽  
pp. 12-21
Author(s):  
Diah Febrina ◽  
Umar Halim
Keyword(s):  
Information Technology ◽  
Social Media ◽  
New Media ◽  
Public Relations ◽  
Mobile Phone ◽  
Tourism Industry ◽  
Tourism Destination ◽  
Tourist Destination ◽  
The World ◽  
Mobile Phone Applications

Globalization has made the inhabitants of the world interconnected more closely in almost every aspect of life because of the speed of information obtained. One of the important things that need to be considered in realizing the process of globalization is the development of information technology. The development of information technology has led to the emergence of new media. The new media is being used in various industries and business including in tourism industry. Public relation practitioners working in tourism industry take benefits of new media as means of communication and promotion. Ragunan Zoo is a tourist destination located in South Jakarta, Indonesia. The development of the era led to the development of strategy in introducing this tourism destination to local and overseas tourists. The types of new media that this tourism destination exploits are websites, social media, and mobile phone applications.

scholarly journals Role of Social Media in Shaping Local Youth Tourists' Behaviour Across the Sri Lankan Tourism Industry

2020 ◽  
pp. 15-22
Author(s):  
H. Shamini
Keyword(s):  
Social Media ◽  
Sri Lanka ◽  
Online Survey ◽  
New Technologies ◽  
Online Reviews ◽  
Tourism Industry ◽  
Sri Lankan ◽  
The People ◽  
Social Media Platforms ◽  
The Mind

The integration of social networking and new technologies has changed the way of communication and information sharing among the people, especially of young people is a fact. As well as, the development of Social Media (SM) has conveyed important changes in the behavioural pattern of tourists. Therefore, it is very essential to understand this new influential trending among the youth tourists, in order to accelerate the tourists’ arrival and contribute to the development of Sri Lanka tourism. Therefore, this research aims at providing an insight to the Tourism Industry in Sri Lanka with regards to how social media platforms influence youth tourists’ behavior. A sample of 103 youth tourists’ response attained through online. The data obtained from the online survey were analyzed with descriptive, reliability test, mean and regression analysis. Results from the survey have identified that Social Media does influence in the youth tourists’ behaviour.  In detail, eWOM and Online reviews/comments significantly influence in the behavior of youth tourists.  And also the study confirmed that in order to attract tourists to a destination mainly revolves in the ability to convey the information to create positive images in the mind of youth tourists via social media. Thereby this study has recommended many suggestions for the Tourism and authorities. Including tourist authority should make its social media pages more interesting, appealing, informative and interactive so the customers can enjoy their social media experiences and they could spread eWOM and online reviews. And also they need to focus on how to create a positive and satisfactory image to their social media users in many other ways.

scholarly journals Analyzing Sentiments and Diffusion Characteristics of COVID-19 Vaccine Misinformation Topics in Social Media

2022 ◽  
Vol 9 (3) ◽  
pp. 1-22
Author(s):  
Mohammad Daradkeh
Keyword(s):  
Social Media ◽  
Data Analytics ◽  
Latent Dirichlet Allocation ◽  
Topic Model ◽  
Diffusion Characteristics ◽  
Sentiment Orientation ◽  
Positive Sentiment ◽  
Negative Sentiment ◽  
And Diffusion ◽  
Machine Learning Models

This study presents a data analytics framework that aims to analyze topics and sentiments associated with COVID-19 vaccine misinformation in social media. A total of 40,359 tweets related to COVID-19 vaccination were collected between January 2021 and March 2021. Misinformation was detected using multiple predictive machine learning models. Latent Dirichlet Allocation (LDA) topic model was used to identify dominant topics in COVID-19 vaccine misinformation. Sentiment orientation of misinformation was analyzed using a lexicon-based approach. An independent-samples t-test was performed to compare the number of replies, retweets, and likes of misinformation with different sentiment orientations. Based on the data sample, the results show that COVID-19 vaccine misinformation included 21 major topics. Across all misinformation topics, the average number of replies, retweets, and likes of tweets with negative sentiment was 2.26, 2.68, and 3.29 times higher, respectively, than those with positive sentiment.

Exploring the Usage of Big Data Analytical Tools in Telecommunication Industry in Oman

Web Services ◽  
2019 ◽  
pp. 459-472
Author(s):  
Himyar Ali Al Jabri ◽  
Ali H. Al-Badi ◽  
Oualid Ali
Keyword(s):  
Information Technology ◽  
Social Media ◽  
Big Data ◽  
Data Management ◽  
Competitive Advantage ◽  
Case Studies ◽  
Telecommunication Industry ◽  
A Value ◽  
Telecom Industry ◽  
Analytical Tools

Big Data has recently become a very hot topic in the field of Information Technology and Data Management. Data generated by the company's daily operations through different resources such as social media, etc. is very important because it can bring a value that will lead to a competitive advantage. The objectives of this research are to: 1) Explore the analytical tools used to manipulate Big Data in Omani telecom industry, 2) Present the benefits of using these tools, the extent of use, and the features specifically promoted these tools, and 3) Highlight the challenges/obstacles that the telecom industry in Oman facing in adopting/using Big Data analytical tools. To achieve the research objectives two case studies were conducted among the main telecom operators in Oman. This research concluded that both studied telecom operators in Oman are not ready for the DBAs. Both operators need to invest in developing the capabilities that enable them to use these tools. Once that is satisfied, then other components like the infrastructure, tools, and data can be managed very well.

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