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

Public network attention to hiking in China and its influencing factors

In the process of hikers' choosing a destination, searching for information is one of the important elements, playing a decisive role in decision-making. Based on the Baidu Index for "hiking," this paper analyzes the spatial and temporal characteristics of and factors that influenced network attention to hiking in China from 2016 to 2021. The study found that (1) Network attention to hiking in China was generally relatively stable across the period studied, with highly uneven distribution between different months. The search volume was higher on weekends, and mobile searches increased year by year, far exceeding computer searches. (2) Different regions in China experienced different levels of network attention, with the highest levels in the east, followed by the center, and the lowest in the west. Except for East China, network attention to hiking was highly unevenly distributed within each region. (3) The COVID-19 pandemic increased the geographical concentration index and coefficient of variation but reduced the primacy index. A region's level of economic development, degree of network development, population size, and population age structure are proposed as factors that affect network attention to hiking.

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

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.

Do Online Reviews Encourage Customers to Write Online Reviews? A Longitudinal Study

This study examines the nature of online reviews to explain changes in satisfaction, trust, and consumer intent to write a review during restaurant revisit stages. Using a data set of two-time lags, the findings show that the impact of online reviews on customer satisfaction, trust, and consumer intent to write a review decreases or dilutes over time. More specifically, the effect of online reviews in T + 1 diminishes as consumers experience a particular restaurant compared to when they initially encountered the review. Our findings also show that the impacts of online reviews on satisfaction and trust gradually decrease over time. However, the relationship between online reviews and trust is only significant in T + 1. Additionally, the effect of trust on customer intent to write a review initially increases (T) and then, gradually drops over time (T + 1). Finally, this study proposes guidelines for improving theoretical and practical insights across consumption experience stages.

A Suggestion on the LDA-Based Topic Modeling Technique Based on ElasticSearch for Indexing Academic Research Results

Most academic researchers use the academic information system when they want to write a reference, such as a related research for a paper. Specific classification rules are applied based on vast amounts of data and the latest references to classify and search keywords. Meta information is designed for specific classification rules and search results are restructured. The search results can be classified and rearranged to suit academic research paper keywords by applying the restructured classification system and the LDA-based topic modeling technique. To implement this, the ElasticSearch classification method and topic-based LDA model were applied to extract the characteristics of academic papers in this study. Stable topics that could detect topic estimation and keyword search results within the minimum time were extracted to classify the paper search results. In addition, by analyzing the distribution of document weight among topics, the system performance was proven to be excellent.

Topic Modelling for Ski Resorts: An Analysis of Experience Attributes and Seasonality

Knowing how to improve skiers’ experiences in ski resorts is vital for developing the ski industry. This study aims to provide a holistic understanding of the key attributes of skiers’ experiences and explore them in the context of seasonality. Based on the user-generated content of 14 ski resorts and the topic modelling and sentiment analysis method, a framework of skiing experience attributes was built. Compared with the seasonal data, the dynamic of skiers’ concerns and perceived performance was revealed. The skiers’ concerns in peak seasons and off seasons manifested different orientations. The results show that the relatively important attributes tend to have relatively low performance in the peak seasons. In off seasons, skiers emphasise non-skiing-oriented attributes. This study showcases that skier’s interests and evaluations of various experience attributes vary with seasons. The findings help to understand the skiers’ peak and supporting experiences, which could be used to build ski resorts management and seasonal hedging strategies.