Exploiting Heterogenous Web Data – A Systematic Approach on the Example of Nintendo Switch Games

Author(s)
Sandra Boric, Christine Strauss
Abstract

This paper shows how heterogenous web data can be retrieved from global yet regionally tailored online platforms such as Amazon. A systematic data retrieval approach was applied to obtain data from regional Amazon and Nintendo websites. The data retrieval uses a 3x3 criteria setting: Three attributes (genre, age rating, player-count), three forms of analysis (distribution, reception, price), and three countries (Germany, U.S.A., Japan). A streamlined choice of Amazon-entries is suggested, and further criteria were set to allow comparisons between different regions. 196 Nintendo Switch games and 15 game genres were analysed. The results show which attributes accumulate the highest numbers of Amazon-ratings and rating scores in which country, and which genres have the highest Amazon- and Nintendo-prices. An uncovering of rating and pricing similarities and differences is of value to game research scholars and game developer studios and aids in a targeted catering to customers in different regions.

Organisation(s)
Department of Marketing and International Business
External organisation(s)
Karl-Franzens-Universität Graz
Pages
69-73
No. of pages
5
DOI
https://doi.org/10.1145/3487664.3487674
Publication date
2021
Peer reviewed
Yes
Austrian Fields of Science 2012
502007 E-commerce, 502019 Marketing, 502050 Business informatics
Keywords
ASJC Scopus subject areas
Human-Computer Interaction, Computer Networks and Communications, Computer Vision and Pattern Recognition, Software
Sustainable Development Goals
SDG 3 - Good Health and Well-being
Portal url
https://ucrisportal.univie.ac.at/en/publications/exploiting-heterogenous-web-data--a-systematic-approach-on-the-example-of-nintendo-switch-games(238e3143-9192-4b08-8e3d-77b2ad27c944).html