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This study collects big data from Twitter, and discover patterns and insight to determine the perception of gentrification and it’s pattern over time as well as sentiments to words gentrification using IBM Watson Analytics. The discovered insights reveal that the interest on the topic is going down in 2017 from years 2015, and nearly 70% of the tweets have a neutral opinion towards gentrification with only a 2% points difference between negative and positive sentiment. The results reveal that in cities with larger, progressive cities, positive sentiments were greater than in cities considered to be within the bible belt -- southern and southeastern states. There may be a correlation between education level and gentrification based on these finding. Therefore, this research demonstrated that artificial intelligence (AI) based solution allow us to discover useful insights from big data created from social media postings and gives a meaningful platform for further discovery. The implication of the results are policy makers need to consider and discover insights from social media while making policies and decision that affect citizens.

data analytics, gentrification, Watson analytics, sentiment analysis