Abstract— With the rapid growth of the internet, millions of people are sharing their views and opinions on a variety of topics on microblogging sites, as it contains simple expressions. Microblogging websites are just social media sites to which user makes real time short and frequent posts about everything. In big event gathering like Hajj, to get rapid and accurate views and impressions of hajji about some quality of service or other views is of a great importance as time and space are limited. In this paper, we utilize tweets during Hajj to do sentiment analysis; the tweets are preprocessed by experience three phases; tokenization, normalization, and part of speech (POS) tagging. In the final step, Naïve Bayes classifier used to classify tweet as positive or negative by comparing each word in the query tweet with the labeled words in the lexicon.
Keywords— Naïve Bayes Classifier, Performance Analysis, Sentiment Analysis, Twitter.
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