KMITL

Permanent URI for this communityhttps://dspace.kmitl.ac.th/handle/123456789/1

Browse

Settings

Subject: search.filters.subject.Online Reviews

Search Results

Now showing 1 - 2 of 2
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Simplified Approach to Constructing Coherent Topics and Subtopics from Text Data: A Case Study Using University Reviews
    (2024-01-01)
    Tunyut, Wuttipong
    ;
    Wanitjirattikal, Puntipa
    This study introduces a streamlined framework for analyzing hierarchical topic structures in text data, integrating Latent Dirichlet Allocation (LDA), Word2Vec, Bigram phasing, Doc2Vec, and hierarchical clustering. The method ensures both statistical coherence and practical interpretability while avoiding the complexities of traditional hierarchical topic models. Applied to university reviews from various educational platforms, this data offers valuable insights into user experiences but presents challenges due to its unstructured nature. Our framework reveals key topics and sentiment variations: positive feedback highlights facilities and cultural experiences, while negative reviews emphasize workload, academic challenges, and financial pressures, identifying areas for improvement. This approach is particularly effective for moderately sized datasets with well-defined scopes, such as university reviews, where the subject matter is clearly understood.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Analysis of Shopping Mall Tourist Satisfaction in Bangkok Using Word Cloud of Online Reviews
    (2023-01-01)
    Ladkoom, Kobthong
    ;
    Tarigan, Emiya Fefayosa Br
    ;
    Yasirandi, Rahmat
    ;
    Suwastika, Novian Anggis
    ;
    Anom, Rahmat Indra Pratama
    The tourism industry is very important to prioritize, especially for developing countries like Thailand. The increase in tourist visits to Bangkok also triggers the potential for a rise in Bangkok tourism during the pandemic. In this study, shopping malls are one of the attractive attractions for a capital city like Bangkok. Tourist expectations of attraction must be realized so that satisfaction can be realized and created revisit. In the digitalization era, the internet's use to find and disseminate information has become commonplace. Tripadvisor.com is one of the leading review sites, which already has many reviewers, and is the case study in this research. Using Word Cloud as an analysis technique and clustering of data reviews, several important factors influence tourist satisfaction. Based on the 1186 clustered reviewers, several factors were produced, such as Place Quality, Location Access, Support Facilities, Price, and Seller Attitude. These factors can influence the decision to visit shopping malls in Bangkok because they represent tourist satisfaction.