Can you make your own trip more cozy by using data science?
Content
The csv file contains 17 fields. The description of each field is as below:
1.Hotel_Address: Address of hotel.
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Review_Date: Date when reviewer posted the corresponding review.
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Average_Score: Average Score of the hotel, calculated based on the latest comment in the last year.
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Hotel_Name: Name of Hotel
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Reviewer_Nationality: Nationality of Reviewer
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Negative_Review: Negative Review the reviewer gave to the hotel. If the reviewer does not give the negative review, then it should be: 'No Negative'
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ReviewTotalNegativeWordCounts: Total number of words in the negative review.
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Positive_Review: Positive Review the reviewer gave to the hotel. If the reviewer does not give the negative review, then it should be: 'No Positive'
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ReviewTotalPositiveWordCounts: Total number of words in the positive review.
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Reviewer_Score: Score the reviewer has given to the hotel, based on his/her experience
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TotalNumberofReviewsReviewerHasGiven: Number of Reviews the reviewers has given in the past.
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TotalNumberof_Reviews: Total number of valid reviews the hotel has.
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Tags: Tags reviewer gave the hotel.
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dayssincereview: Duration between the review date and scrape date.
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AdditionalNumberof_Scoring: There are also some guests who just made a scoring on the service rather than a review. This number indicates how many valid scores without review in there.
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lat: Latitude of the hotel
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lng: longtitude of the hotel