Antecedents of Loyalty in Mobile Social Network Games

Chan, Delphine Ya-Chu; Xing, Zeng-Liang; Zhang, Zhihao

doi:10.2991/ichssd-17.2018.27

Cited by 1 publication

(1 citation statement)

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“…For examples, Caci et al ( 2018 ) analyzed players who play “Pokémon GO”, discussed the interaction between players’ play motivation, player’s personality, and play habits, and conducted research on individual differences in play motivation and personality characteristics. The work of Chan et al ( 2017 ) shows the information, interactivity, and entertainments of mobile games have a positive impact on the trust and loyalty of players. Hsiao and Chen ( 2016 ) identified the factors that affect the perceived value and loyalty of games, including fun, flexibility of play time, interactivity, and rich rewards.…”

Section: Literature Reviewmentioning

confidence: 99%

The key successful factors of video and mobile game crowdfunding projects using a lexicon-based feature selection approach

Chen

Chang

Chen

et al. 2021

J Ambient Intell Human Comput

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The emergence of crowdfunding has given many capital demanders a new fund-raising channel, but the overall project success rate is very low. Many scholars have begun to discover key suscessful factors of crowdfunding projects. Previous studies have used questionnaires survey to identify important project features. In addition to requiring a lot of manpower and time, there may also be sampling bias. Moreover, related studies also reported that the project description will affect the success of the crowdfunding project, but there is no research to tell fundraisers which success factors should be included in the content of the project description. Besides, in recent years, game crowdfunding projects have been attracted lots of attention in terms of total fundraising amount and number of projects. Moreover, in traditional feature selection and text mining approaches, the selected terms are un-organized and hard to be explained. Therefore, this study will focus on real video and mobile game project descriptions to replace conventional questionnaires. To solve these issues, we present a lexicon-based feature selection method. We attempt to define “content features” and build lexicons to determine the attributes’ values. Three feature selection methods including decision tree (DT), Least Absolute Shrinkage and Selection Operator (LASSO), and support vector machine–recursive feature elimination (SVM–RFE) will be employed to find organized candidate key successful factors. Then, support vector machines (SVM) will be used to evaluate the performances of candidate feature subsets. Finally, this study has identified the key successful factors for video and mobile games, respectively. Based on the experimental results, we can give fundraisers some useful suggestions to improve the success rate of crowdfunding projects.

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Section: Literature Reviewmentioning

confidence: 99%