The data set refers to a small corpus of messages or tweets mentioning seven
major hotel brands. It was gathered by continuously querying and archiving
the Twitter Streaming API service, using the
R. A total of 7,296 tweets were extracted within a time period of 6 days, from June 23th to June 28th 2013. Only tweets in the English language were considered. A sentiment polarity variable was calculated, indicating the sentiment value of each message and a third variable, user visibility or popularity, as measured by
the number of followers each user had, was also included in the dataset
A data frame with the following variables:
The hotel brand mentioned in the tweet: 1=Hilton, 2=Intercontinental, 3=Marriott, 4=Bestwestern, 5=Starwood, 6=Hyatt, 7=Choice
Sentiment for each tweet: 1=negative (-), 2=mixed (+/-), 3=positive (+), 4=very positive (++)
User popularity/visibility in Twitter: 1=low, 2=medium, 3=high
Iodice D' Enza, A., & Markos, A. (2015). Low-dimensional tracking of association structures in categorical data, Statistics and Computing, 25(5), 1009-1022.
Iodice D'Enza, A., Markos, A., & Buttarazzi, D. (2018). The idm Package: Incremental Decomposition Methods in R. Journal of Statistical Software, Code Snippets, 86(4), 1–24. DOI: 10.18637/jss.v086.c04.
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