Big Data Analytics to Analyze Sentiment, Emotions, and Perceptions of Travelers (Case Study: Tourism Destination in Purwokerto Indonesia)
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Abstract
Big data analytics can extract travelers' sentiment, emotions, and experiences from their internet opinions. This study analyzes sentiment, emotion, and traveler experiences at eight tourism destinations in Purwokerto Central Java, Indonesia. The methods are lexicon using NCR vocabulary(EmoLex) and word cloud analysis. The results show visitors generally have a positive sentiment. The five destinations with high positive sentiment are the Village (91%), Lokawisata Baturaden(81%), Baturaden Forest (79%), Limpa Kuwus (78%), and Taman Andang(.77%). In comparison, other destinations achieve positive sentiment under 70%. Only a few visitors give negative sentiment to all tourism destinations. The emotion of visitors stands out in Joy and Trust. NRC revealed sadness dan anger emotion but only about 20%. Cloud analysis does not reveal a distinguish keyword because the word feature still contained noise such as conjunction, adverb, and the name of the sites. Further research must consider other text preprocessing to handle noises.
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