Topic Modeling for Hiking Trail Online Reviews: Analysis of the Mutianyu Great Wall

Shang, Ziye; Luo, Jian Ming

doi:10.3390/su14063246

Cited by 13 publications

(6 citation statements)

References 65 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Researchers no longer need to manually code and interpret data due to statistical validation. As a result, topic modeling has been extensively used in several disciplines, including geography (Shang et al , 2022; Qiao and Williams, 2022), political science (Dehler-Holland et al , 2022; Miranda and Bringula, 2021; Bogović et al , 2021), hospitality and tourism (Shang and Luo, 2022; Wu et al , 2022; Kwon et al , 2022; Mishra et al , 2021; Kirilenko et al , 2021; Lee et al , 2021; Mariani and Baggio, 2021), education (Waheeb et al , 2022; Vijayan, 2021) and medical science (Porturas and Taylor, 2021), among others. Its use in business research, though, has been relatively sparse.…”

Section: Methodsmentioning

confidence: 99%

Decoding mood of the Twitterverse on ESG investing: opinion mining and key themes using machine learning

Jaiswal,

Gupta,

Tiwari

2024

MRR

View full text Add to dashboard Cite

Purpose Grounded in the stakeholder theory and signaling theory, this study aims to broaden the research agenda on environmental, social and governance (ESG) investing by uncovering public sentiments and key themes using Twitter data spanning from 2009 to 2022. Design/methodology/approach Using various machine learning models for text tonality analysis and topic modeling, this research scrutinizes 1,842,985 Twitter texts to extract prevalent ESG investing trends and gauge their sentiment. Findings Gibbs Sampling Dirichlet Multinomial Mixture emerges as the optimal topic modeling method, unveiling significant topics such as “Physical risk of climate change,” “Employee Health, Safety and well-being” and “Water management and Scarcity.” RoBERTa, an attention-based model, outperforms other machine learning models in sentiment analysis, revealing a predominantly positive shift in public sentiment toward ESG investing over the past five years. Research limitations/implications This study establishes a framework for sentiment analysis and topic modeling on alternative data, offering a foundation for future research. Prospective studies can enhance insights by incorporating data from additional social media platforms like LinkedIn and Facebook. Practical implications Leveraging unstructured data on ESG from platforms like Twitter provides a novel avenue to capture company-related information, supplementing traditional self-reported sustainability disclosures. This approach opens new possibilities for understanding a company’s ESG standing. Social implications By shedding light on public perceptions of ESG investing, this research uncovers influential factors that often elude traditional corporate reporting. The findings empower both investors and the general public, aiding managers in refining ESG and management strategies. Originality/value This study marks a groundbreaking contribution to scholarly exploration, to the best of the authors’ knowledge, by being the first to analyze unstructured Twitter data in the context of ESG investing, offering unique insights and advancing the understanding of this emerging field.

show abstract

Section: Methodsmentioning

confidence: 99%

Decoding mood of the Twitterverse on ESG investing: opinion mining and key themes using machine learning

Jaiswal,

Gupta,

Tiwari

2024

MRR

View full text Add to dashboard Cite

show abstract

“…Hiking is considered an activity chosen by travelers when visiting other places [8] and is an area development option because it can combine services such as accommodation and food facilities [9]. Usually, hiking is accompanied by contact with nature in areas where there are monuments and natural attractions, by the exploration of new areas [10], and by visiting protected areas [11].…”

Section: Literature Reviewmentioning

confidence: 99%

Attitudes and Views of Citizens Regarding the Contribution of the Trail Paths in Protection and Promotion of Natural Environment

Kantartzis

Lemonakis

Malesios

et al. 2022

Land

View full text Add to dashboard Cite

In recent decades, large sections of trail paths throughout Greece have been maintained, revived, and marked, creating a wide network with a total length of approximately 3500 km. The trail paths are one of the main levers of tourism development as they contribute to the preservation, protection, and promotion of the countryside, cultural heritage, and tradition, to the more effective protection and management of areas of exceptional natural beauty and sensitive ecosystems with wildlife. This paper investigates the view of the citizens of the regional unit of Evros, Greece, on the contribution of the trail paths to the protection and promotion of the cultural and natural environment. The research was conducted with the use of a structured questionnaire and through personal interviews. The data were collected and analyzed with the use of descriptive statistical methods as well as multivariate analysis techniques. The results of the research show that the attitudes of citizens to the contribution of paths in the protection and promotion of the cultural and natural environment are directly or indirectly influenced by various factors. In particular, age directly affects the view of citizens towards the trail paths, with the younger ones having more positive views. Other important predictors of citizens’ views were the type of activity in the trail path, with citizens using them for leisure activities or using the easy roots having more positive views towards them.

show abstract

“…The national parks need to be profitable and environmentally friendly. Hiking is one of the most popular and interesting outdoor hobbies [13][14][15], and one of the most basic and important activities in national parks and other outdoor recreation areas. Although hiking was once considered a niche activity, it has become a popular outdoor sport [16].…”

Section: Introductionmentioning

confidence: 99%

Who behaves more pro-environmental in the national parks: A comparison of the tourist and the hiker

et al. 2023

View full text Add to dashboard Cite

The intention of pro-environmental behavior (PEB) directly affects the sustainable development of protected areas, especially national parks, but few studies have done comparative research on tourist and hiker behaviors. This study explores the intention of tourists’ and hikers’ pro-environmental behavior based on theory of planned behavior (TPB) and norm activation theory (NAM). Researchers surveyed 454 tourists and 466 hikers in Wuyishan National Park a structural equation modeling data analysis method. The results demonstrate that the TPB and the NAM were accurate in describing for tourists’ and hikers’ pro-environmental behavior in national park. However, for specific influencing factors, hikers’ attitude, awareness of consequences, and assumption of responsibility were significantly different from those of the tourists. This study sheds light on how to better comprehend and advocate for PEB in national parks and proposes different management approaches to improve the PEB of tourists and hikers.

show abstract

Topic Modeling for Hiking Trail Online Reviews: Analysis of the Mutianyu Great Wall

Cited by 13 publications

References 65 publications

Decoding mood of the Twitterverse on ESG investing: opinion mining and key themes using machine learning

Decoding mood of the Twitterverse on ESG investing: opinion mining and key themes using machine learning

Attitudes and Views of Citizens Regarding the Contribution of the Trail Paths in Protection and Promotion of Natural Environment

Who behaves more pro-environmental in the national parks: A comparison of the tourist and the hiker

Contact Info

Product

Resources

About