In AyrtonRua/group1_project: Package touristR (providing tourist friendly interactive map)

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This vignette summarises the various use cases related to the R package touristR. Most of this information is available scattered throughout the R documentation of each function. The following vignette, summarizes the roles of those different functions, allowing the user to get a large perspective on the goals and implementation of the package.

Package overview

Welcome to the touristR package, this package is available under GPL-2 license, and provided to you as part of the group project of Group 1 (Myama). The goal of the package is to provide a practical guide for tourists interested in exploring the top landmarks of each city in the world using as a reference, twitter comments.
This allows the user to quickly obtain highly relevant suggestions on what are the best places to visit, and how do other people comment about this place. The implementation of this vision is represented by the function run_shiny, which requires in that sense a stable internet connection in order to capture in real time how people are commenting about a given place (i.e. measuring the popularity and the sentiment they have toward a certain place).

The package allows also to determine how are certain keywords (places' names/other) varying in terms of popularity overtime, allowing both tourists to get an overview of how popular different places are (maximum comparison of 4 places in parallel), while also allowing other usages such as analysing for example how are keywords related to brands changing in terms of popularity (measured by the # count), allowing marketers for example to identify when do their brand fans interact the most with the company, and thus determining the best time slots for advertising (i.e. when users are the most engaged).
In that sense the function track_twitter_hashtag automatically aggregates the results per hour/day based on the user input (for time periods less than or equal to 2 weeks the results are presented by hours/for longer timeframes the results are reported by aggregating the # counts per day).

Finally the package provides also the function getTopNAttractions, which provides the data used as a reference to construct the Shiny map, allowing the user to further investigate in a more quantitative way the visual results provided (i.e. the user may analyze how results change over time, which landmarks become more or less popular over time).

Data

• The package uses data from the following sources

• (tweets) obtained via querying the Twitter API

• list of top places per city obtained via querying (webscrapping) TripAdvisor

AyrtonRua/group1_project documentation built on May 14, 2019, 5:14 a.m.