scholarly journals Museum Tourism 2.0: Experiences and Satisfaction with Shopping at the National Gallery in London

2019 ◽  
Vol 11 (24) ◽  
pp. 7108
Author(s):  
Jun Shao ◽  
Qinlin Ying ◽  
Shujin Shu ◽  
Alastair M. Morrison ◽  
Elizabeth Booth

The tourist shopping experience is the sum of the satisfaction or dissatisfaction from the individual attributes of purchased products and services. With the popularity of the Internet and travel review websites, more people choose to upload their tour experiences on their favorite social media platforms, which can influence another’s travel planning and choices. However, there have been few investigations of social media reviews of tourist shopping experiences and especially of satisfaction with museum tourism shopping. This research analyzed the user-generated reviews of the National Gallery (NG) in London written in the English language on TripAdvisor to learn more about tourist shopping experience in museums. The Latent Dirichlet Allocation (LDA) topic model was used to discover the underlying themes of online reviews and keywords related to these shopping experiences. Sentiment analysis based on a purpose-developed dictionary was conducted to explore the dissatisfying aspects of tourist shopping experiences. The results provide a framework for museums to improve shopping experiences and enhance their future development.

2021 ◽  
pp. 147078532110475
Author(s):  
Manit Mishra

The ubiquity of social media platforms facilitates free flow of online chatter related to customer experience. Twitter is a prominent social media platform for sharing experiences, and e-retail firms are rapidly emerging as the preferred shopping destination. This study explores customers’ online shopping experience tweets. Customers tweet about their online shopping experience based on moments of truth shaped by encounters across different touchpoints. We aggregate 25,173 such tweets related to six e-retailers tweeted over a 5-year period. Grounded on agency theory, we extract the topics underlying these customer experience tweets using unsupervised latent Dirichlet allocation. The output reveals five topics which manifest into customer experience tweets related to online shopping—ordering, customer service interaction, entertainment, service outcome failure, and service process failure. Topics extracted are validated through inter-rater agreement with human experts. The study, thus, derives topics from tweets about e-retail customer experience and thereby facilitates prioritization of decision-making pertaining to critical service encounter touchpoints.


2021 ◽  
Author(s):  
Iain Cruickshank ◽  
Tamar Ginossar ◽  
Jason Sulskis ◽  
Elena Zheleva ◽  
Tanya Berger-Wolf

BACKGROUND The onset of the COVID-19 pandemic and the consequent “infodemic” that ensued highlighted the role that social media play in increasing vaccine hesitancy. Despite the efforts to curtail the spread of misinformation, the anti-vaccination movement continues to use Twitter and other social media platforms to advance its messages. Although users typically engage with different social media platforms, research on vaccination discourse typically focused on single platforms. Understanding the content and dynamics of external content shared on vaccine-related conversations on Twitter during the COVID-19 pandemic can shed light on the use of different sources, including traditional media and social media by the anti-vaccination movement. In particular, examining how YouTube videos are shared within vaccination-related tweets is important in understanding the spread of anti-vaccination narratives. OBJECTIVE informed by agenda-setting theory, this study aimed to use machine-learning to understand the content and dynamics of external websites shared in vaccines-related tweets posted in COVID-19 conversations on Twitter. METHODS We screened around 5 million tweets posted to COVID-19 related conversations to include tweets that discussed vaccination. We then identified external content, including the most tweeted web domains and URLs within these tweets and the number of days they were shared. The topics and dynamics of tweeted YouTube videos were further analyzed by using Latent Dirichlet Allocation to topic-model the transcripts of the YouTube videos, and by independent coders. RESULTS of 841,896 vaccination-related tweets identified, 128,408 (22.1%) included external content. A wide range of external websites were shared. The 20 most tweeted websites constituted 10.9% of the shared websites and were typically shared for only 2-3 days within a one-month period. Traditional media constituted the majority of these 20 most tweeted URLs. Content of YouTube links shared had both the greatest number of unique URLs for any given URL domain and was the most tweeted domain over time. The majority (n=15) of the 20 most tweeted videos opposed vaccinations and featured conspiracy theories. Analysis of the transcripts of 1,280 YouTube videos shared indicated high frequency of conspiracy theories. CONCLUSIONS Our study reveals that sharing URLs over Twitter is a common communication strategy. Whereas shared URLs overall demonstrated a strong presence of legacy media organizations, YouTube videos were used to spread anti-vaccination messages. Produced by individuals or by foreign governments, these videos emerged as a major driver for sharing vaccine-related conspiracy theories. Future interventions should take into account cross-platform use to counteract this misinformation.


JMIR Nursing ◽  
10.2196/35274 ◽  
2022 ◽  
Vol 5 (1) ◽  
pp. e35274
Author(s):  
Bhavya Yalamanchili ◽  
Lorie Donelle ◽  
Leo-Felix Jurado ◽  
Joseph Fera ◽  
Corey H Basch

Background During a time of high stress and decreased social interaction, nurses have turned to social media platforms like TikTok as an outlet for expression, entertainment, and communication. Objective The purpose of this cross-sectional content analysis study is to describe the content of videos with the hashtag #covidnurse on TikTok, which included 100 videos in the English language. Methods At the time of the study, this hashtag had 116.9 million views. Each video was coded for content-related to what nurses encountered and were feeling during the COVID-19 pandemic. Results Combined, the 100 videos sampled received 47,056,700 views; 76,856 comments; and 5,996,676 likes. There were 4 content categories that appeared in a majority (>50) of the videos: 83 showed the individual as a nurse, 72 showed the individual in professional attire, 58 mentioned/suggested stress, 55 used music, and 53 mentioned/suggested frustration. Those that mentioned stress and those that mentioned frustration received less than 50% of the total views (n=21,726,800, 46.17% and n=16,326,300, 34.69%, respectively). Although not a majority, 49 of the 100 videos mentioned the importance of nursing. These videos garnered 37.41% (n=17,606,000) of the total views, 34.82% (n=26,759) of the total comments, and 23.85% (n=1,430,213) of the total likes. So, despite nearly half of the total videos mentioning how important nurses are, these videos received less than half of the total views, comments, and likes. Conclusions Social media and increasingly video-related online messaging such as TikTok are important platforms for social networking, social support, entertainment, and education on diverse topics, including health in general and COVID-19 specifically. This presents an opportunity for future research to assess the utility of the TikTok platform for meaningful engagement and health communication on important public health issues.


2021 ◽  
Author(s):  
Bhavya Yalamanchili ◽  
Lorie Donelle ◽  
Leo-Felix Jurado ◽  
Joseph Fera ◽  
Corey H Basch

BACKGROUND During a time of high stress and decreased social interaction, nurses have turned to social media platforms like TikTok as an outlet for expression, entertainment, and communication. OBJECTIVE The purpose of this cross-sectional content analysis study is to describe the content of videos with the hashtag #covidnurse on TikTok, which included 100 videos in the English language. METHODS At the time of the study, this hashtag had 116.9 million views. Each video was coded for content-related to what nurses encountered and were feeling during the COVID-19 pandemic. RESULTS Combined, the 100 videos sampled received 47,056,700 views; 76,856 comments; and 5,996,676 likes. There were 4 content categories that appeared in a majority (>50) of the videos: 83 showed the individual as a nurse, 72 showed the individual in professional attire, 58 mentioned/suggested stress, 55 used music, and 53 mentioned/suggested frustration. Those that mentioned stress and those that mentioned frustration received less than 50% of the total views (n=21,726,800, 46.17% and n=16,326,300, 34.69%, respectively). Although not a majority, 49 of the 100 videos mentioned the importance of nursing. These videos garnered 37.41% (n=17,606,000) of the total views, 34.82% (n=26,759) of the total comments, and 23.85% (n=1,430,213) of the total likes. So, despite nearly half of the total videos mentioning how important nurses are, these videos received less than half of the total views, comments, and likes. CONCLUSIONS Social media and increasingly video-related online messaging such as TikTok are important platforms for social networking, social support, entertainment, and education on diverse topics, including health in general and COVID-19 specifically. This presents an opportunity for future research to assess the utility of the TikTok platform for meaningful engagement and health communication on important public health issues.


2021 ◽  
Author(s):  
Danny Valdez ◽  
Jennifer B Unger

BACKGROUND In 2018, JUUL Labs Inc, a popular e-cigarette manufacturer, announced it would substantially limit its social media presence in compliance with the Food and Drug Administration’s (FDA) call to curb underage e-cigarette use. However, shortly after the announcement, a series of JUUL-related hashtags emerged on various social media platforms, calling the effectiveness of the FDA’s regulations into question. OBJECTIVE The purpose of this study is to show that hashtags remain a common venue to market age-restricted products on social media. METHODS We used Twitter’s standard Application Programming Interface (API) to download the 3200 most-recent tweets originating from JUUL Labs Inc.’s official Twitter Account (@JUULVapor), and a series of tweets containing one, or more, of the following hashtags (#ecig, #vape, #JUUL). We ran two Latent Dirichlet Allocation (LDA) topic models comparing @JUULVapor’s content versus our hashtag corpus. We qualitatively deliberated topic meanings and substantiated our interpretations with tweets from either corpus. RESULTS The topic model generated for @JUULVapor’s timeline seemingly alluded to compliance with the FDA’s call to prohibit marketing of age-restricted products on social media. However, the topic model generated for the hashtag corpus contained several references to flavors, vaping paraphernalia, and illicit drugs which may be appealing to younger audiences. CONCLUSIONS Our findings underscore the complicated nature of social media regulation. Although JUUL Labs Inc. seemingly complied with the FDA to limit its social media presence, JUUL and other e-cigarette manufacturers are still discussed openly in social media spaces. Much discourse about JUUL and e-cigarettes is spread via hashtags, which allow messages to reach a wide audience quickly. This suggests social media regulations on manufacturers are, by themselves, in effective. Stricter protocols are needed to regulate discourse about age-restricted products on social media.


2021 ◽  
Vol 27 (3) ◽  
pp. 200-213
Author(s):  
Yuen Chi Phang ◽  
Azleena Mohd Kassim ◽  
Ernest Mangantig

Objectives: The main aim of this study was to use text mining on social media to analyze information and gain insight into the health-related concerns of thalassemia patients, thalassemia carriers, and their caregivers.Methods: Posts from two Facebook groups whose members consisted of thalassemia patients, thalassemia carriers, and caregivers in Malaysia were extracted using the Data Miner tool. In this study, a new framework known as Malay-English social media text pre-processing was proposed for performing the steps of pre-processing the noisy mixed language (Malay-English language) of social media posts. Topic modeling was used to identify hidden topics within posts shared among members. Three different topic models—latent Dirichlet allocation (LDA) in GenSim, LDA in MALLET, and latent semantic analysis—were applied to the dataset with and without stemming using Python.Results: LDA in MALLET without stemming was found to be the best topic model for this dataset. Eight topics were identified within the posts shared by members. Of those eight topics, four were newly discovered by this study, and four others corresponded to the findings of previous studies that used an interview approach.Conclusions: Topic 2 (the challenges faced by thalassemia patients) was found to be the topic with the highest attention and engagement. Healthcare practitioners and other concerned parties should make an effort to build a stronger support system related to this issue for those affected by thalassemia.


2021 ◽  
pp. 016344372110158
Author(s):  
Opeyemi Akanbi

Moving beyond the current focus on the individual as the unit of analysis in the privacy paradox, this article examines the misalignment between privacy attitudes and online behaviors at the level of society as a collective. I draw on Facebook’s market performance to show how despite concerns about privacy, market structures drive user, advertiser and investor behaviors to continue to reward corporate owners of social media platforms. In this market-oriented analysis, I introduce the metaphor of elasticity to capture the responsiveness of demand for social media to the data (price) charged by social media companies. Overall, this article positions social media as inelastic, relative to privacy costs; highlights the role of the social collective in the privacy crises; and ultimately underscores the need for structural interventions in addressing privacy risks.


Author(s):  
Linh Nguyen ◽  
Kim Barbour

This paper explores whether or not our online social media persona is viewed as authentic. The selfie is a fundamental part of the structure of the online identity for young people in today’s digital world. The relationship between an individual’s self-identity in the physical face-to-face environment was analysed and compared to a carefully constructed, modified virtual representation in a selfie posted on social media platforms. Data was obtained through four focus groups at the University of Adelaide. Two key theoretical frameworks provide a basis for this study: Erving Goffman’s concept of the self as a performance, and Charles Horton Cooley’s concept of the looking glass self. In examining the focus group discussions in light of these two frameworks as well as associated literature, we conclude that the authenticity of the selfie as a way of visualising a social media persona is subjective and dependent on the individual posting a selfie. Ultimately, authenticity involves a degree of subjectivity. It was on this basis that focus group participants argued that selfies could be considered authentic expressions of identity.


2021 ◽  
Vol 37 (1) ◽  
pp. 207-217
Author(s):  
Clara Matheus Nogueira

William Shakespeare is one of the greatest authors of the English language and is present in multiple school curricula. However, reading Shakespeare in classrooms can be a challenge for both teachers and students. In schools, adaptations from literature to social media platforms, such as #dream40, a production by the Royal Shakespeare Company, remain not fully explored. In this paper, this production is presented as a possible ally in the effort of bringing the English canon closer to the students’ reality, making the Bard more engaging and accessible, since this production uses mechanics that are part of most students’ daily lives on social networking platforms, such as the hashtag that appears in the title of this production; besides, #dream40 is closely aligned with our contemporary paradigm of worldview.


2020 ◽  
Author(s):  
Junze Wang ◽  
Ying Zhou ◽  
Wei Zhang ◽  
Richard Evans ◽  
Chengyan Zhu

BACKGROUND The COVID-19 pandemic has created a global health crisis that is affecting economies and societies worldwide. During times of uncertainty and unexpected change, people have turned to social media platforms as communication tools and primary information sources. Platforms such as Twitter and Sina Weibo have allowed communities to share discussion and emotional support; they also play important roles for individuals, governments, and organizations in exchanging information and expressing opinions. However, research that studies the main concerns expressed by social media users during the pandemic is limited. OBJECTIVE The aim of this study was to examine the main concerns raised and discussed by citizens on Sina Weibo, the largest social media platform in China, during the COVID-19 pandemic. METHODS We used a web crawler tool and a set of predefined search terms (<i>New Coronavirus Pneumonia</i>, <i>New Coronavirus</i>, and <i>COVID-19</i>) to investigate concerns raised by Sina Weibo users. Textual information and metadata (number of likes, comments, retweets, publishing time, and publishing location) of microblog posts published between December 1, 2019, and July 32, 2020, were collected. After segmenting the words of the collected text, we used a topic modeling technique, latent Dirichlet allocation (LDA), to identify the most common topics posted by users. We analyzed the emotional tendencies of the topics, calculated the proportional distribution of the topics, performed user behavior analysis on the topics using data collected from the number of likes, comments, and retweets, and studied the changes in user concerns and differences in participation between citizens living in different regions of mainland China. RESULTS Based on the 203,191 eligible microblog posts collected, we identified 17 topics and grouped them into 8 themes. These topics were pandemic statistics, domestic epidemic, epidemics in other countries worldwide, COVID-19 treatments, medical resources, economic shock, quarantine and investigation, patients’ outcry for help, work and production resumption, psychological influence, joint prevention and control, material donation, epidemics in neighboring countries, vaccine development, fueling and saluting antiepidemic action, detection, and study resumption. The mean sentiment was positive for 11 topics and negative for 6 topics. The topic with the highest mean of retweets was domestic epidemic, while the topic with the highest mean of likes was quarantine and investigation. CONCLUSIONS Concerns expressed by social media users are highly correlated with the evolution of the global pandemic. During the COVID-19 pandemic, social media has provided a platform for Chinese government departments and organizations to better understand public concerns and demands. Similarly, social media has provided channels to disseminate information about epidemic prevention and has influenced public attitudes and behaviors. Government departments, especially those related to health, can create appropriate policies in a timely manner through monitoring social media platforms to guide public opinion and behavior during epidemics.


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