A Big Data Analytics Framework for analyzing global tourism trends of Indians using Social Media Analytics
作者
Kamal Kumar Ranga,Chander Kumar Nagpal
标识
DOI:10.1109/ccict56684.2022.00021
摘要
While planning to visit a place it is very difficult to decide any place based on our preferences that may include, availability of veg food or weather a place is family friendly or not. Searching out such place is really a cumbersome task which involves going around good number of websites and social media platforms and reading never ending reviews. To cater this evolving issue an innovative and simple solution is proposed in this paper. Here, Data is extracted from world famous and most authentic travel website TripAdvisor, where most of users post their experiences in form of review about the place they have visited in natural language text. The system extracts these reviews and analyzes with the help of machine learning model based on five factors that are of common concern like Veg_food availability, Family_friendliness, other_facilities, destination and hotels around etc., based on user’s true experiences. The system generates likeness score on the scale of 0 to 1, for each destination to visit on the basis of these metrics and an overall rating is represented visually for the ease of future user.