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Record W3176934125

Emerging Scholar Profile-Dr. Danielle Barbe

2021· article· en· W3176934125 on OpenAlexaboutno aff
Danielle Barbe

Bibliographic record

VenueEreview of tourism research · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Relations and Crisis Communication
Canadian institutionsnot available
Fundersnot available
KeywordsHospitalitySocial mediaTourismSociologyContext (archaeology)Public relationsMedia studiesPolitical scienceHistory
DOInot available

Abstract

fetched live from OpenAlex

Dr. Danielle Barbe is a Lecturer in Digital Marketing in the Faculty of Business and Law, at Newcastle Business School, Northumbria University. Danielle earned her PhD in Tourism, Hospitality, and Event Management and a minor in Communications from the University of Florida in spring 2020. Danielle’s overarching research area is in tourism and digital communications, examining ways to enhance the communications efforts between tourists and tourism suppliers. Danielle’s research examines the capabilities of digital communication tools in the context of tourism, with the goal of developing theoretically driven and empirically tested strategies that incorporate web, social, and mobile technologies. Through this research, Danielle has studied concepts relating to crisis communication, technology acceptance and use, persuasion, credibility, misinformation, electronic word-of-mouth (eWOM), engagement, relationship marketing, and influencer marketing Danielle’s academic journey and passion for research began at Ryerson University in Toronto, Canada where she was a Research Assistant for Dr. Kelly MacKay at the Institute for Hospitality and Tourism Research. In this role, Danielle conducted research on social media use and engagement in festival and event settings. Danielle’s experience with research at this time was limited. However, the more she learned, the more she wanted to continue to learn and discover answers to what was still unknown about this area. Danielle continued her academic journey at the University of Florida where her background on social media research took on the new lens of crisis communication. Working with Dr. Lori Pennington-Gray and the Tourism Crisis Management Initiative (TCMI), Danielle began evaluating the current state of online crisis communication by the tourism industry. The goal was to understand what organisations are communicating to tourists on social media in times of crisis. She analysed social media content by Destination Management Organisations (DMOs), hotels, the media, and publics. Danielle also analysed social media communication during a variety of crises (terrorist attacks, hurricanes, disease outbreaks, organisational-level crises) in multiple countries, including USA, UK, France, Belgium, Spain, Germany, and Sri Lanka. These studies were conducted as a situational analysis, to grasp a better understanding of current crisis communication. However, in these studies, Danielle found that, overall, the tourism industry was inept at communicating to tourists on social media during these times. Many DMOs and hotels were not only actively avoid communicating on social media about the crisis, but used an ineffective messaging strategy, focused heavily on recovery rather than tourists’ safety. Using these insights, Danielle’s dissertation titled ‘Developing a crisis communication model for the tourism industry: The effects of source, media, and time’ adopted a communications-focused approach to create a research-driven strategy that informs the tourism industry on how to increase visitors’ safety in times of crisis. Danielle’s dissertation focused on a terrorism-related crisis and consisted of three studies addressing each critical element of effective communication: source, medium, message and time. The purpose was to understand who the most influential sources are during a terrorist attack, which media tourists are most likely to turn to, when crisis communication is most necessary, and how message type can impact perceptions of safety and security at the destination. Danielle’s dissertation research informs destination managers on how to optimise their social media strategy by understanding how tourists behave on a variety of platforms during a crisis and how the messages by the tourism organisation may elicit a different response by the tourist. Each study provides unique elements to understand the communications process during a crisis in a tourism destination. Using the results from this research, Danielle is currently developing a crisis communication template to support tourism destinations’ crisis communication strategies.   While Danielle’s primary research specialism is social media and crisis communication, Danielle’s overall research covers a wider spectrum. Danielle’s broader research agenda focuses on the use of digital technologies for the marketing, management, and development of tourism. Under the umbrella of communications, Danielle focuses on the factors influencing the persuasive effects of communication, looking particularly at the effects of source, media, message, and time on the attitudes and behaviours of the receiver. Her research extends beyond communication as a marketing tool, evaluating a range of communication options in the management, practice, and policy of tourism. Danielle acknowledges that tourism is a complex system, and thus examines communications from both a supply and demand perspective, focusing on strategies by the communicator as well as its effects on the receiver of messages. A recent research interest has been on influencer marketing, specifically through visually-centred platforms, such as Instagram. Influencer marketing has seen tremendous growth in recent years, however the research on this lucrative area is scarce, particularly in tourism. Danielle is exploring this area in depth to understand (1) why tourists follow influencers, (2) how tourists perceive influencers, and (3) the effects and outcomes of influencer marketing. In addition, Danielle has recently published research on the perceived credibility of misinformation on visually-focused social media platforms. Danielle is a strong believer in interdisciplinary collaboration and is actively engaged in partnerships with colleagues from universities in Canada, USA, and throughout Europe. Danielle is also a member of the Travel and Tourism Research Association and International Communications Association. Now part of the digital marketing team at Northumbria University, Danielle is excited for opportunities to work with colleagues across a broad area of specialisations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.755
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.132
GPT teacher head0.482
Teacher spread0.351 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2021
Admission routes1
Has abstractyes

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