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提升哈尔滨冰雪旅游目的地竞争力:基于情感分析和潜在狄利克雷分配的大规模数据研究

Enhancement of Harbin ice and snow tourism destination competitiveness: A large-scale data study based on sentiment analysis and Latent Dirichlet Allocation.

作者信息

Jiang Bin, Zhang Chunxiang, Cui Yingyin, Zhu JiuLian, Liu Zhennan

机构信息

College of Science, Shihezi University, Shihezi, People's Republic of China.

College of Marxism, Dali University, Dali, People's Republic of China.

出版信息

PLoS One. 2025 Mar 21;20(3):e0319435. doi: 10.1371/journal.pone.0319435. eCollection 2025.

Abstract

In recent years, the ice and snow tourism industry has exhibited a concurrent state of vigorous expansion and intense rivalry. Strengthening competitiveness is of paramount significance for attaining a dominant position in the market. Thus, this study endeavors to dissect the multi-dimensional determinants of the competitiveness of ice and snow tourism destinations from the demand perspective and establish an evaluation framework. Leveraging 48,420 tourist reviews sourced from ten highly reputed ice and snow tourist attractions in Harbin, text features were extracted via the application of Term Frequency - Inverse Document Frequency (TF-IDF). Subsequently, the Latent Dirichlet Allocation (LDA) topic model was deployed to precisely extract key themes. The sentiment inclination was gauged by SnowNLP. Eventually, the Importance - Performance (IPA) model was utilized to analyze the strengths and weaknesses of the ice and snow tourism competitiveness. The outcomes are as follows: (1) Seven prominent themes, namely tourist activities, environment, resources, historical and cultural aspects, cost - performance, service, and experience, were recognized as potent driving forces. (2) Tourists manifested positive emotions and a high degree of approval. (3) The competitiveness score of the Harbin ice and snow tourism destination was determined to be 0.64, with tourist activities constituting the advantage, whereas resources and environment necessitating enhancement. This study transcends the constraints of traditional supply-side-centered research. Innovatively, tourist sentiment was integrated into the evaluation system, thereby augmenting the connotations of the competitiveness evaluation model. Based on the LDA topic clustering results, sentiment analysis was conducted, enhancing the accuracy of portraying tourists' inner experiences. Concrete and forward-looking strategic recommendations were proffered for augmenting the competitiveness of ice and snow tourism destinations, thereby furnishing theoretical and practical guidance for the high-quality progression of ice and snow tourism.

摘要

近年来,冰雪旅游业呈现出蓬勃发展与激烈竞争并存的态势。增强竞争力对于在市场中占据主导地位至关重要。因此,本研究力图从需求视角剖析冰雪旅游目的地竞争力的多维度决定因素,并构建一个评价框架。利用从哈尔滨十个著名冰雪旅游景点收集的48420条游客评论,通过应用词频 - 逆文档频率(TF-IDF)提取文本特征。随后,运用潜在狄利克雷分配(LDA)主题模型精确提取关键主题。借助SnowNLP衡量情感倾向。最终,采用重要性 - 绩效(IPA)模型分析冰雪旅游竞争力的优势与劣势。结果如下:(1)七个突出主题,即旅游活动、环境、资源、历史文化方面、性价比、服务和体验,被确认为强大驱动力。(2)游客表现出积极情绪和高度认可。(3)哈尔滨冰雪旅游目的地的竞争力得分为0.64,其中旅游活动构成优势,而资源和环境有待提升。本研究突破了传统以供给侧为中心的研究局限。创新地将游客情感融入评价体系,从而丰富了竞争力评价模型的内涵。基于LDA主题聚类结果进行情感分析,提高了描绘游客内心体验的准确性。为提升冰雪旅游目的地竞争力提供了具体且具有前瞻性的战略建议,从而为冰雪旅游的高质量发展提供理论和实践指导。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e46/11927900/831a00648704/pone.0319435.g001.jpg

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