Dataset: Viewing Airbnb from Twitter: factors associated with users' utilization

Published: 15-06-2021| Version 1 | DOI: 10.17632/g6sk4z4fbw.1
Contributor:
Phoey Lee Teh

Description

A total of 21,097 tweets was collected in a period of two months, and the tweets were qualitatively analyzed with the help of text analysis tools to verify the discourse of discussion. Literature was reviewed for common factors attracting clients to an Airbnb accommodation. Phoey Lee Teh, Yeh Ching Low, and Pei Boon Ooi. 2020. Viewing Airbnb from Twitter: factors associated with users' utilization. In Proceedings of the 22nd International Conference on Information Integration and Web-based Applications & Services (iiWAS '20). Association for Computing Machinery, New York, NY, USA, 274–281. DOI:https://doi.org/10.1145/3428757.3429112

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Step 1 - The data set was obtained from the Twitter website (https://twitter.com/home/). Step 2 - Tweets tagged with #Airbnb hashtags were compiled. Output - A total of 21,097 review comments from March 2019 to May 2019. Details of Data analysis and interpretation is discuss in section 3.3 of this article (publicly accessible) Phoey Lee Teh, Yeh Ching Low, and Pei Boon Ooi. 2020. Viewing Airbnb from Twitter: factors associated with users' utilization. In Proceedings of the 22nd International Conference on Information Integration and Web-based Applications & Services (iiWAS '20). Association for Computing Machinery, New York, NY, USA, 274–281. DOI:https://doi.org/10.1145/3428757.3429112 URL - https://dl.acm.org/doi/10.1145/3428757.3429112