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Project: Text Mining and Semantic Analysis for a Yelp Restaurant Reviews Dataset

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Yelp-Review-Analysis-And-Prediction

Implementation of Topic Modeling To Uncover Hidden Strengths and Weaknesses of Restaurants

The Dataset Format looks as follows:

  1. Business Data:

{'address': '691 Richmond Rd', 'attributes': {'BikeParking': True, 'BusinessParking': {'garage': False, 'lot': True, 'street': False, 'valet': False, 'validated': False}, 'RestaurantsPriceRange2': 2, 'WheelchairAccessible': True}, 'business_id': 'YDf95gJZaq05wvo7hTQbbQ', 'categories': ['Shopping', 'Shopping Centers'], 'city': 'Richmond Heights', 'hours': {'Friday': '10:00-21:00', 'Monday': '10:00-21:00', 'Saturday': '10:00-21:00', 'Sunday': '11:00-18:00', 'Thursday': '10:00-21:00', 'Tuesday': '10:00-21:00', 'Wednesday': '10:00-21:00'}, 'is_open': 1, 'latitude': 41.5417162, 'longitude': -81.4931165, 'name': 'Richmond Town Square', 'neighborhood': '', 'postal_code': '44143', 'review_count': 17, 'stars': 2.0, 'state': 'OH'}

  1. Review Data

{'business_id': 'dQZOCI_IIxrUKPnRa56yog', 'cool': 0, 'date': '2017-01-13', 'funny': 0, 'review_id': 'tSgCahyLXjHjMWQyCHrQ8g', 'stars': 2, 'text': 'Hit and miss with food quality - maybe it depends on who is cooking that day. We were there in Dec 2016 and ordered the Walleye dinner and Gyros plate. LOVED both - perfectly cooked and delicious. If I had written this review then, it would be 5 stars. However we went again last week (Jan 2017), ordered the same identical plates and were totally disappointed. Everything was underdone. The walleye, fries, gyro meat, pita = all undercooked and not hot. We probably should have returned it all. Doubt if we will take a chance again.', 'useful': 0, 'user_id': 'rOKLo5-U4HTg_q3tV1nbbg'}

  1. User Data

{'average_stars': 3.8, 'compliment_cool': 5174, 'compliment_cute': 284, 'compliment_funny': 5174, 'compliment_hot': 5175, 'compliment_list': 78, 'compliment_more': 299, 'compliment_note': 1435, 'compliment_photos': 7829, 'compliment_plain': 7397, 'compliment_profile': 569, 'compliment_writer': 1834, 'cool': 16856, 'elite': [2014, 2016, 2013, 2011, 2012, 2015, 2010, 2017], 'fans': 209, 'friends': ['M19NwFwAXKRZzt8koF11hQ',...], 'funny': 16605, 'name': 'Cin', 'review_count': 272, 'useful': 17019, 'user_id': 'lsSiIjAKVl-QRxKjRErBeg', 'yelping_since': '2010-07-13'}

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Project: Text Mining and Semantic Analysis for a Yelp Restaurant Reviews Dataset

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