Browsing by Author "Shoowa, Johannes."

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    SOCIAL MEDIA SENTIMENT ANALYSIS FOR TOURISM PROMOTION IN NAMIBIA
    (Namibia University of Science and Technology, 2025-08-12) Shoowa, Johannes.
    The rapid evolution of the Internet and advancements in information and communication technologies (ICT) have drastically changed how consumers share experiences and opinions, particularly in the tourism industry. Specialised social media platforms such as TripAdvisor now serve as primary channels through which tourists express their views via Electronic Word-of-Mouth (eWOM), significantly influencing the decisions of potential visitors. Despite Namibia’s growing reputation as a tourist destination, there has been limited exploration into how tourists' opinions shared on specialised social media platforms can be systematically analysed to inform marketing strategies. Existing work in sentiment analysis has proven its value across multiple sectors, but its application within the tourism industry, particularly in Namibia, remains underexplored. This research builds upon previous studies that have utilised artificial intelligence (AI) and machine learning (ML) for sentiment classification and prediction but innovates by applying these techniques specifically to tourism promotion in Namibia. This study investigates the application of sentiment analysis, utilising AI and machine learning techniques, to enhance tourism promotion in Namibia. Data was scraped from TripAdvisor, a specialised social media review platform, using Instant Data Scraper. Relevant reviews were filtered to retain only those directly related to Namibian tourism. Data pre-processing included cleaning, tokenisation, stopword removal, and standardisation to prepare the text for sentiment classification. Sentiment analysis was then conducted using Natural Language Processing (NLP) tools, namely the Valence Aware Dictionary and sEntiment Reasoner (VADER) and the RoBERTa model from Hugging Face. These tools were employed to classify user-generated content into positive, negative, and neutral sentiment categories to facilitate analysis. The results from this study reveal insightful trends in tourist perceptions. Positive sentiments frequently highlight Namibia’s natural beauty, wildlife, and unique cultural experiences as standout attractions. In contrast, negative sentiments often relate to issues such as inconsistent service quality, poor infrastructure in remote areas, and occasional dissatisfaction with customer service. These insights not only validate the value of applying sentiment analysis in this context but also uncover specific areas that require attention for improvement. These findings, specifically the positive perceptions of Namibia’s natural attractions and the negative feedback on service quality and infrastructure, can help tourism stakeholders craft targeted, data-driven marketing strategies. Additionally, a strategy that addresses areas of concern while amplifying the country's strengths can enhance Namibia's appeal as a top travel destination and contribute to the sustainable growth of its tourism industry.