User Influence, Hashtag Trends, and Engagement Patterns: Analyzing Social Media Network Dynamics in Tourism Using Graph Analytics

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Thank you for the opportunity to review this paper, which seeks to highlight the dynamics of social media in the tourism industry, with a particular focus on user influence, hashtag trends, and engagement patterns through a variety of methodological approaches, with NodeXL for visualization and clustering analysis being the most prominent. This helped gain insights into community structures as well as interaction dynamics.

 

a)      Abstract; The researcher mentioned that various methodological approaches were used and only one was mentioned. I suggest mentioning other methodological approaches that were used if they were used.

b)      Introduction: The introduction provides a clear vision of the impact of social media on tourism using social network analysis, but it suffers from some repetition and disorganization, which affects the smoothness of the presentation. The references used also need updating, especially with regard to advanced data analytics in tourism, with the need to clarify how to integrate quantitative and qualitative analysis to achieve a deeper understanding of influence patterns and digital engagement. There is an overlap between ideas, as sustainability, hashtag trends, and user influence are addressed without a clear logical connection, which calls for restructuring the introduction to enhance coherence. In addition, the academic formulation should be improved and inaccurate statements avoided, with a focus on research gaps and a clearer highlighting of scientific contribution.

c)       Tourism Network Dynamics and 1.2. Hashtags Trends and Engagement Patterns in Tourism: I suggest integrating it with the literature review. This section provides important insights into the dynamics of tourism networks and the impact of hashtags on digital engagement, but it suffers from repetition and weak methodological coherence, with a lack of updating of references and clarity of practical application of geographical and network analysis. The examples presented, such as the Notre Dame fire, also need to be more clearly linked to tourism and tourism marketing strategies rather than focusing on general social analysis. It is necessary to reorganize the text, update references, and strengthen the link between methodology and graphic analysis to ensure the strength and clarity of the research proposal.

d)      Literature review: This section suffers from disorganization and repetition in some places, which reduces the clarity of the central idea. There is an inconsistent integration of theoretical studies and practical applications, as digital analysis tools such as NodeXL and graphical analysis are mentioned without explaining how they are used in practice to understand the dynamics of tourism networks. Some references, such as (Gössling et al., 2007), need to be updated to ensure that the research is aligned with the latest trends in digital tourism. In addition, the importance of emotional and visual storytelling and its impact on consumer behavior is addressed, but without an in-depth analysis of how it can be employed in sustainable marketing strategies. The text also lacks an integrated theoretical framework that links social network analysis to sustainable tourism governance, making it necessary to restructure it to reflect a clearer logical sequence between previous studies and current research contributions.

e)      Methodology: In this section, concepts such as centrality, geodesic spacing, and modularity are introduced without sufficient justification for their selection as key criteria for analysis. The focus on user statistics and their influence in the network also lacks a direct link to sustainable tourism, which calls for clarification of how these analyses can be exploited to guide tourism marketing or governance strategies. Some references, such as (Casanueva et al., 2016; Partelow & Nelson, 2020), need to be updated or strengthened with more recent research that reflects developments in digital tourism data analytics. Furthermore, mentioning digital outputs such as user rankings and centrality scores without a deeper analysis of their impact on destination strategies makes the results seem purely technical without clear practical applications. It is therefore necessary to reorganize the methodology, simplify technical terms, and clarify how the results contribute to improving sustainable tourism to enhance the academic value of the study.

f)        Results: This section is characterized by a lack of coherence between concepts and an abundance of statistical data without in-depth analysis, which makes it purely theoretical. There is a repetition in presenting the evolution of hashtags without clarifying their relationship with tourism marketing and sustainability. Also, the statistics provided lack a clear explanation of how they affect digital tourism. The graphical visualizations need qualitative analysis and stronger linkage to marketing trends. Therefore, it is preferable to reorganize this section, simplify the terminology, and clarify the practical applications to enhance the research value.

g)       Discussion: The discussion addresses the influence of users in tourism social networks using graphical analysis, but it suffers from repetition and inconsistent presentation, as the same concepts such as user centrality and the influence of hashtags are mentioned multiple times without adding new insights. Also, the discussion on the role of social influencers lacks a more in-depth analysis of how they influence tourism behavior and sustainability, and this should be more clearly linked to tourism marketing trends and environmental responsibility. Moreover, this section focuses excessively on statistics and quantitative results without providing a qualitative analysis that explains the context of these results, which reduces the practical value of the study. Discussing the temporal evolution of networks and the impact of emotional narratives also needs to clarify how they can be used to improve tourism marketing campaigns rather than simply pointing out their existence. Finally, the discussion of methodological limitations should be strengthened and deeper suggestions for future studies should be included, such as sentiment analysis and exploring newer platforms such as TikTok. Thus, the text needs to be reorganized, more closely linked to tourism reality, and more in-depth qualitative analysis to enhance the research value.

h)      Conclusion: The conclusion provides a comprehensive summary of the study’s objectives and findings, but it suffers from repetition and disorganization, which reduces the clarity of the final message. Despite providing an in-depth analysis of the role of data analytics in understanding digital tourism dynamics, some concepts such as the social influence of hashtags and influential users are repeated without adding new value. Discussing practical applications, such as leveraging influencers and digital marketing strategies, also needs to be more explicit about how these recommendations can be practically implemented in sustainable tourism. Furthermore, pointing out research limitations such as not using sentiment analysis or excluding newer platforms such as TikTok is an important point, but it needs clearer suggestions for how to overcome them in future studies. Finally, the link between theory and practice could be improved by highlighting how data analysis can be used in practice to improve digital tourism policies. Therefore, it is recommended to restructure the conclusion, reduce repetition, and strengthen the link between findings and practical recommendations to ensure a more coherent vision and stronger academic benefit.

Author Response

Thank you for the opportunity to review this paper, which seeks to highlight the dynamics of social media in the tourism industry, with a particular focus on user influence, hashtag trends, and engagement patterns through a variety of methodological approaches, with NodeXL for visualization and clustering analysis being the most prominent. This helped gain insights into community structures as well as interaction dynamics.

1. a) Abstract; The researcher mentioned that various methodological approaches were used and only one was mentioned. I suggest mentioning other methodological approaches that were used if they were used.

Response: Revised, please see the attached revision.

1. b) Introduction: The introduction provides a clear vision of the impact of social media on tourism using social network analysis, but it suffers from some repetition and disorganization, which affects the smoothness of the presentation. The references used also need updating, especially with regard to advanced data analytics in tourism, with the need to clarify how to integrate quantitative and qualitative analysis to achieve a deeper understanding of influence patterns and digital engagement. There is an overlap between ideas, as sustainability, hashtag trends, and user influence are addressed without a clear logical connection, which calls for restructuring the introduction to enhance coherence. In addition, the academic formulation should be improved and inaccurate statements avoided, with a focus on research gaps and a clearer highlighting of scientific contribution.

Response: Revised, please see the attached revision.

1. c) Tourism Network Dynamics and 1.2. Hashtags Trends and Engagement Patterns in Tourism: I suggest integrating it with the literature review. This section provides important insights into the dynamics of tourism networks and the impact of hashtags on digital engagement, but it suffers from repetition and weak methodological coherence, with a lack of updating of references and clarity of practical application of geographical and network analysis. The examples presented, such as the Notre Dame fire, also need to be more clearly linked to tourism and tourism marketing strategies rather than focusing on general social analysis. It is necessary to reorganize the text, update references, and strengthen the link between methodology and graphic analysis to ensure the strength and clarity of the research proposal.

Response: Revised, please see the attached revision.

1. d) Literature review: This section suffers from disorganization and repetition in some places, which reduces the clarity of the central idea. There is an inconsistent integration of theoretical studies and practical applications, as digital analysis tools such as NodeXL and graphical analysis are mentioned without explaining how they are used in practice to understand the dynamics of tourism networks. Some references, such as (Gössling et al., 2007), need to be updated to ensure that the research is aligned with the latest trends in digital tourism. In addition, the importance of emotional and visual storytelling and its impact on consumer behavior is addressed, but without an in-depth analysis of how it can be employed in sustainable marketing strategies. The text also lacks an integrated theoretical framework that links social network analysis to sustainable tourism governance, making it necessary to restructure it to reflect a clearer logical sequence between previous studies and current research contributions.

Response: Revised, please see the attached revision.

1. e) Methodology: In this section, concepts such as centrality, geodesic spacing, and modularity are introduced without sufficient justification for their selection as key criteria for analysis. The focus on user statistics and their influence in the network also lacks a direct link to sustainable tourism, which calls for clarification of how these analyses can be exploited to guide tourism marketing or governance strategies. Some references, such as (Casanueva et al., 2016; Partelow & Nelson, 2020), need to be updated or strengthened with more recent research that reflects developments in digital tourism data analytics. Furthermore, mentioning digital outputs such as user rankings and centrality scores without a deeper analysis of their impact on destination strategies makes the results seem purely technical without clear practical applications. It is therefore necessary to reorganize the methodology, simplify technical terms, and clarify how the results contribute to improving sustainable tourism to enhance the academic value of the study.

Response: Revised, please see the attached revision.

1. f) Results: This section is characterized by a lack of coherence between concepts and an abundance of statistical data without in-depth analysis, which makes it purely theoretical. There is a repetition in presenting the evolution of hashtags without clarifying their relationship with tourism marketing and sustainability. Also, the statistics provided lack a clear explanation of how they affect digital tourism. The graphical visualizations need qualitative analysis and stronger linkage to marketing trends. Therefore, it is preferable to reorganize this section, simplify the terminology, and clarify the practical applications to enhance the research value.

Response: Revised, please see the attached revision.

1. g) Discussion: The discussion addresses the influence of users in tourism social networks using graphical analysis, but it suffers from repetition and inconsistent presentation, as the same concepts such as user centrality and the influence of hashtags are mentioned multiple times without adding new insights. Also, the discussion on the role of social influencers lacks a more in-depth analysis of how they influence tourism behavior and sustainability, and this should be more clearly linked to tourism marketing trends and environmental responsibility. Moreover, this section focuses excessively on statistics and quantitative results without providing a qualitative analysis that explains the context of these results, which reduces the practical value of the study. Discussing the temporal evolution of networks and the impact of emotional narratives also needs to clarify how they can be used to improve tourism marketing campaigns rather than simply pointing out their existence. Finally, the discussion of methodological limitations should be strengthened and deeper suggestions for future studies should be included, such as sentiment analysis and exploring newer platforms such as TikTok. Thus, the text needs to be reorganized, more closely linked to tourism reality, and more in-depth qualitative analysis to enhance the research value.

Response: Revised, please see the attached revision.

1. h) Conclusion: The conclusion provides a comprehensive summary of the study’s objectives and findings, but it suffers from repetition and disorganization, which reduces the clarity of the final message. Despite providing an in-depth analysis of the role of data analytics in understanding digital tourism dynamics, some concepts such as the social influence of hashtags and influential users are repeated without adding new value. Discussing practical applications, such as leveraging influencers and digital marketing strategies, also needs to be more explicit about how these recommendations can be practically implemented in sustainable tourism. Furthermore, pointing out research limitations such as not using sentiment analysis or excluding newer platforms such as TikTok is an important point, but it needs clearer suggestions for how to overcome them in future studies. Finally, the link between theory and practice could be improved by highlighting how data analysis can be used in practice to improve digital tourism policies. Therefore, it is recommended to restructure the conclusion, reduce repetition, and strengthen the link between findings and practical recommendations to ensure a more coherent vision and stronger academic benefit.

Response: Revised, please see the attached revision.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

This is a well-written study exploring social media network dynamics to uncover hidden patterns. And, the methodology is based on data analytics which give real-worlds insights about the topic. I have noted below some points to improve. 

The abstract should provide a general to specific background by introducing the focus of study on social media dynamics on toursim. Next, please clearly state your purpose in the abstract, then introduce your methodology. In the final part of the abstract, briefly summarize the results and the practical / managerial / theoretical contributions of this paper. 

Introduction is ok. Here, please also include the background info, your motivation to conduct such study, the gap in the literature, your purpose, your methodology, and the reason why this methodology is selected in this research, your research questions, your findings in brief, and then the info about the next sections as paragraphs. Since there are many industrial reports emphasizing the importance of the topic, please present more to convince the audience that this paper is really needed for the literature. 

Sections 1.1. Tourism Network Dynamics and 1.2. Hashtags Trends and Engagement Patterns in Tourism must be included to Literature Review. 

Besides, a summarizing table in the literature is a must for this paper. Please, here provide a table includeing these studies methodologies and findings in brief. This kind of literature summaries improves the chance of your work's getting cited. Additionally, please ensure that each paragraph has a clear main idea. Some sections are dense with information and could benefit from clearer topic sentences. Avoid overly technical jargon unless necessary. Simplify complex terms for broader accessibility. Organize the literature review into sub-sections with clear headings (e.g., “Role of Social Media,” “Social Network Analysis,” “Sustainable Tourism Practices”. Use bullet points or numbered lists to highlight key findings or important studies for easier readability.

In the methodology, you give some general explanations about the SNA. But, what about the mathematics of it? Please explain this technique in detail.

3.2. Data Collection is ok. 

in the lines 339 and 340, there are

3.3. Data Analysis

Graph Analytics in Tourism

Please correct this sub-title. Is it only Data Analysis?

The remaining parts are ok. However, the figures can be more clear for reading. 

In the conclusion, Please state your practical, managerial and theoretical contributions in detail. And the further research ideas should be improved. 

 

 

 

Author Response

This is a well-written study exploring social media network dynamics to uncover hidden patterns. And, the methodology is based on data analytics which give real-worlds insights about the topic. I have noted below some points to improve. 

The abstract should provide a general to specific background by introducing the focus of study on social media dynamics on tourism. Next, please clearly state your purpose in the abstract, then introduce your methodology. In the final part of the abstract, briefly summarize the results and the practical / managerial / theoretical contributions of this paper. 

Response: Revised, please see the attached revision.

The introduction is ok. Here, please also includes the background info, your motivation to conduct such study, the gap in the literature, your purpose, your methodology, and the reason why this methodology is selected in this research, your research questions, your findings in brief, and then the info about the next sections as paragraphs. Since there are many industrial reports emphasizing the importance of the topic, please present more to convince the audience that this paper is really needed for literature. 

Response: Revised, please see the attached revision.

Sections 1.1. Tourism Network Dynamics and 1.2. Hashtags Trends and Engagement Patterns in Tourism must be included to Literature Review. 

Response: Revised, please see the attached revision.

Besides, a summarizing table in the literature is a must for this paper. Please, here provide a table includeing these studies methodologies and findings in brief. This kind of literature summaries improves the chance of your work's getting cited. Additionally, please ensure that each paragraph has a clear main idea. Some sections are dense with information and could benefit from clearer topic sentences. Avoid overly technical jargon unless necessary. Simplify complex terms for broader accessibility. Organize the literature review into sub-sections with clear headings (e.g., “Role of Social Media,” “Social Network Analysis,” “Sustainable Tourism Practices”. Use bullet points or numbered lists to highlight key findings or important studies for easier readability.

Response: Revised, please see the attached revision.

In the methodology, you give some general explanations about the SNA. But, what about the mathematics of it? Please explain this technique in detail.

3.2. Data Collection is ok. 

in the lines 339 and 340, there are

3.3. Data Analysis

Graph Analytics in Tourism

Please correct this sub-title. Is it only Data Analysis?

The remaining parts are ok. However, the figures can be more clear for reading. 

In the conclusion, Please state your practical, managerial and theoretical contributions in detail. And the further research ideas should be improved. 

Response: Revised, please see the attached revision.

 

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

Dear authors

Thank you for the job. 

Meanwhile, please have a look at some of the remarks:

line 67: we insist on checking the necessity of the word "while" twice: While Dickinson et al. While Wu et al. (2013),...

line 137: please, remember not to have any contractions in a formal text - "These networks aren't fixed;"

line 220 We aske the authors to explain the use of "to" in: Casanueva et al. (2016), to demonstrate that SNA is useful in revealing how the propagation of the relationships between tourists, service providers, and public institutions can 221 affect the functioning and development of the tourism ecosystem.

line 236 The sentence needs a verb: Dickinson et al. (2014), on the influence of our electronic and social groups on progressive tourism and the connection between community life and mobile technology. 

line 462: we suggest choosing another adverb to escape tautology: The graph visualizations visually demonstrated the communication behavior 

I would like to suggest changing the color in Fig. 3 to an easily seen one.

Comments on the Quality of English Language

There were some issues that we highlight in the Authors' section to be rewritten or revised, concerning the language.

Author Response

Meanwhile, please have a look at some of the remarks:

line 67: we insist on checking the necessity of the word "while" twice: While Dickinson et al. While Wu et al. (2013),...

Response: Revised, please see the attached revision.

line 137: please, remember not to have any contractions in a formal text - "These networks aren't fixed;"

Response: Revised, please see the attached revision.

line 220 We aske the authors to explain the use of "to" in: Casanueva et al. (2016), to demonstrate that SNA is useful in revealing how the propagation of the relationships between tourists, service providers, and public institutions can 221 affect the functioning and development of the tourism ecosystem.

Response: Revised, please see the attached revision.

line 236 The sentence needs a verb: Dickinson et al. (2014), on the influence of our electronic and social groups on progressive tourism and the connection between community life and mobile technology. 

Response: Revised, please see the attached revision.

line 462: we suggest choosing another adverb to escape tautology: The graph visualizations visually demonstrated the communication behavior 

I would like to suggest changing the color in Fig. 3 to an easily seen one.

Response: Revised, please see the attached revision.

There were some issues that we highlight in the Authors' section to be rewritten or revised, concerning the language.

Response: Revised, please see the attached revision.

 

Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

The paper highlights the dynamics of social media (SM) networks in the tourism industry, focusing on specific aspects of user influence, hashtag trends, and engagement patterns. The authors quantify structural metrics such as centrality, modularity and geodesic distances to illustrate the interrelation between users. The paper shows that digital narratives influence tourism trends and direct tourism preferences within the network. The authors point out that utilising this information has helpful managerial implications. This information may help improve destination branding, design sustainable tourism practices, and promote targeted research. The paper is informative but requires some revisions before publication in Tourism and Hospitality.

1. The paper's introduction needs further work. The authors should show, in more detail, how SM influences consumer behaviour and determines the demand for tourism destinations.
2. Adopting Social Network Analysis (SNA) requires the digital transformation of Small and Medium Enterprises (SMEs). What are the challenges for SMEs? The authors should discuss them as they propose managerial implications. Two papers are informative: https://doi.org/10.1007/s13132-024-02300-5 and https://doi.org/10.1016/j.techsoc.2024.102483.
3. The authors note that social media and its dynamics have greatly influenced sustainable development in the tourism and hospitality industry. The authors should stress this linkage. Various papers discuss this relationship. For instance, what is the role of classical political economy in directing sustainable development, and how is this influence promoted through SM?
4. Figures 1, 2, 3, 4, and 5 should not be images. I advise the authors to create them using a proper programme.
5. Figures 5, 6 and 7 need titles.  
6. The authors should add a separate section to discuss the paper's theoretical and policy implications.
7. Similarly, they should add a section to present the paper's limitations.    

Author Response

The paper highlights the dynamics of social media (SM) networks in the tourism industry, focusing on specific aspects of user influence, hashtag trends, and engagement patterns. The authors quantify structural metrics such as centrality, modularity and geodesic distances to illustrate the interrelation between users. The paper shows that digital narratives influence tourism trends and direct tourism preferences within the network. The authors point out that utilising this information has helpful managerial implications. This information may help improve destination branding, design sustainable tourism practices, and promote targeted research. The paper is informative but requires some revisions before publication in Tourism and Hospitality.

1. The paper's introduction needs further work. The authors should show, in more detail, how SM influences consumer behaviour and determines the demand for tourism destinations.

Response: I have corrected it. Please find the attached file.

2. Adopting Social Network Analysis (SNA) requires the digital transformation of Small and Medium Enterprises (SMEs). What are the challenges for SMEs? The authors should discuss them as they propose managerial implications. Two papers are informative: https://doi.org/10.1007/s13132-024-02300-5 and https://doi.org/10.1016/j.techsoc.2024.102483.

Response: Please check the discussion part.

3. The authors note that social media and its dynamics have greatly influenced sustainable development in the tourism and hospitality industry. The authors should stress this linkage. Various papers discuss this relationship. For instance, what is the role of classical political economy in directing sustainable development, and how is this influence promoted through SM?

Response: The relationship between classical political economy and sustainable development in tourism and hospitality is multifarious, with social media (SM) functioning as the quintessential medium for influence. Classical political economy understands the significant roles played by government policy, market forces and institutional settings in shaping economic activities (including tourism). From a sustainable development standpoint, this view emphasizes the role of regulatory frameworks, economic incentives, and stakeholder engagement in fostering practices that reconcile economic development with environmental sustainability and social equity. By enabling information sharing, stakeholder meetings, opinion solicitation, and social media magnifies the elements of classical political economy. SM is also used by government institutions and tourism bodies to advertise sustainable tourism projects and practices in the industry, as well as to reach the other side of the market, including researchers, media, and general audiences. Another example is the United Nations World Tourism Organization (UNWTO), which uses social media to promote sustainable tourism policies and showcases best practices worldwide.

Furthermore, social media is a marketplace for sustainable tourism products and services, with definitions and consumption of them reflecting market dynamics central to political economy. Because SM provides a platform for tourism enterprises to promote green accommodation, eco-friendly tour packages, and community-based tourism experiences, which stimulates consumer awareness and guides consumers to choose more sustainable options. The trend towards eco-conscious consumption drives businesses to adopt sustainability practices to compete in the market, demonstrating how the market drives sustainable practices.

4. Figures 1, 2, 3, 4, and 5 should not be images. I advise the authors to create them using a proper programme.

Response: Students enrolled in the Social Network Analysis course receive a license to use NodeXL software for their analysis. Unfortunately, I do not currently have access to a license, which limits my ability to perform a proper analysis.

5. Figures 5, 6 and 7 need titles.  

Response: I fixed it.

6. The authors should add a separate section to discuss the paper's theoretical and policy implications.

Response:

Theoretical Implications

Through the use of SNA and graph-based analytics, this study extends existing research on digital tourism and the analytics of social media. Findings extend conceptual discussions on multiple axes of relevance:

• Social Media Influence in Tourism Networks:

In addition, this research contributes to the existing theoretical corpus surrounding networked influence by illustrating the role of key opinion leaders, influencers and engaged users in shaping tourism discourses. Although previous research has examined the role of influences on consumer engagement in tourism, this study goes beyond qualitative insights and, for the first time, quantifies these relationships via centrality measures, namely degree and betweenness centrality.

• Hashtag Evolution and Thematic Propagation:

Those insights help us better understand the life cycle of hashtags, and how some tourism related hashtags are being used and emerging over time. This helps build on media diffusion theory, highlighting the progress of digital conversations and revealing how the changing nature of tourism narratives is played out through the popularity of hashtags.

• Engagement Patterns and Digital Narratives:

This study highlights recent research related digital storytelling in tourism by identifying engagement trends. This underscores the relationship between visual and written storytelling and supports theoretical frameworks around emotional contingencies and consumer choice in digital arenas.

• Graph Analytics as a Methodological Advancement in Tourism Research:

The graph-based methods presented provide a quantitative approach to exploring the digital tourism networks. In contrast to traditional content analysis or sentiment analysis, graph analytics allows a structural analysis of online interaction, blending a computational social science approach with tourism studies.

Policy Implications

Network influence insights can guide policymakers in creating targeted marketing campaigns. Destination marketers know to identify and leverage high-centrality users, optimizing the promotional action and maximum attention. The co-occurrence analysis of sustainability-related hashtags (e.g., #SustainableTourism, #EcoTravel) indicates an increasing interest in environmentally responsible travel. This trend can be leveraged by policymakers by integrating sustainability messaging in digital campaigns and fostering sustainable travel policies. This is a case study of the Notre Dame Fire and the way social media becomes a rapid response tool for crisis communication. Comment: Tourist boards and civil authorities could create frameworks for monitoring social media engagement in times of crisis, and incorporate these insights into their disaster recovery strategies.

Policymakers may find it useful to have ethical standards and regulations in place concerning influencer marketing, since social media marketing increasingly shapes the travel choices people make, making it imperative that tourism marketing follows ethical and responsible tourism guidelines. The trend analysis of the study’s engagement provides policymakers with real-time insights into travel behavior. Understanding seasonal trends in hashtag utilization can enable tourism boards to adjust resource allocation, forecast fluctuations in demand, and improve planning for tourism infrastructure.

7. Similarly, they should add a section to present the paper's limitations.    

Response: This research provides important insights into the evolution of tourism-focused social media networks through graph analysis yet has a number of limitations. The analysis is largely based on Twitter (X) data and may not be representative of engagement trends on visual heavy platforms like Instagram and TikTok. Moreover, the research is limited to cross-sectional data, preventing it from evaluating changes in user behavior over time. No sentiment analysis provides a richer understanding of the emotional tone of user interactions, and the results might get affected by algorithmic biases favoring some voices over others. Graph analytics offers a structural view but not a qualitative one, leaving it almost impossible to interpret the reasons underlying engagement trends. In addition, the study's policy suggestions, while meaningful, might be difficult to carry out, owing to challenges like budget limitations and regulatory obstacles. Venture sentiment analysis, longitudinal data, qualitative methods and broadening the scope to other social media platforms will help us better understand the mechanisms of digital tourism engagement.

 

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The author made a great effort to address the suggestions. The paper became clearer and more in-depth.

I have no further questions or suggestions.

Good luck

Author Response

It is a significant achievement for me, and it would not have been possible without the invaluable support of the reviewers. I sincerely appreciate their guidance and expertise.

Reviewer 2 Report

Comments and Suggestions for Authors

The required revisions are fulfilled. 

Author Response

Good to hear it.

Reviewer 3 Report

Comments and Suggestions for Authors

Dear authors 

Thank you very much for doing this good job.

Author Response

All credit goes to you. Thank you so much.

Reviewer 4 Report

Comments and Suggestions for Authors

The authors addressed most of my comments. However, it would be informative to enhance their discussion of SMEs' challenges. 

Author Response

Thank you so much. I was very busy with my study as well as my assistantship. My apologies for this inconvenience. 

Round 3

Reviewer 4 Report

Comments and Suggestions for Authors

The authors addressed my previous comments and improved their manuscript.