Tourism and Travel Content Analysis for Market Segmentation using Toxicity and Sentiment Classification in Communalytic

Abstract

This research highlights the significant impact of digital content on shaping tourist perceptions and behaviors, particularly emphasizing the influence of travel vlogs. Utilizing the Tourism and Travel Content Analysis (TTCA) framework, the study analyzed 1,972 review posts out of 2,250, revealing critical insights into viewer engagement and sentiment. Toxicity score calculations indicated prevalent negative interactions, with scores ranging from 0.05542 to 0.86967 for Toxicity, 0.00536 to 0.50704 for Severe Toxicity, 0.01921 to 0.59834 for Identity Attack, 0.03305 to 0.76573 for Insult, 0.03737 to 0.78492 for Profanity, and 0.01075 to 0.48617 for Threat, underscoring the need for compelling content moderation. Sentiment analysis using VADER and TextBlob demonstrated a generally positive reception of travel vlogs, with VADER classifying 3.73% of posts as unfavorable, 19.83% as neutral, and 76.44% as positive. In comparison, TextBlob classified 2.71% of posts as unfavorable, 35.59% as neutral, and 61.69% as positive for English posts. Notably, VADER and TextBlob agreed on sentiment classification for 446 out of 587 posts (75.98%), with a Cohen’s kappa statistic of 0.471, indicating moderate agreement. These findings suggest that well-regulated and thoughtfully designed digital content significantly enhances user engagement and optimizes destination marketing strategies. Future research should incorporate advanced analytical tools and comprehensive data sets to refine these insights further, supporting the development of more targeted and effective marketing efforts in the tourism sector. This study thus contributes to a deeper understanding of digital media's impact on tourism marketing, offering practical recommendations for leveraging content to foster positive and engaging tourist experiences