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This study explores tweets from Oct 2008 to Oct 2018 related to halal tourism. The tweets were extracted from twitter and underwent various cleaning processes. A total of 33,880 tweets were used for analysis. Analysis intended to (1) identify the topics users tweet about regarding halal tourism, and (2) analyze the emotion-based sentiment of the tweets. To identify and analyze the topics, the study used a word list, concordance graphs, semantic network analysis, and topic-modeling approaches. The NRC emotion lexicon was used to examine the sentiment of the tweets. The analysis illustrated that the word “halal” occurred in the highest number of tweets and was primarily associated with the words “food” and “hotel”. It was also observed that non-Muslim countries such as Japan and Thailand appear to be popular as halal tourist destinations. Sentiment analysis found that there were more positive than negative …